Databases or Datasets for Computer Vision Applications and Testing

Generally, to avoid confusion, in this bibliography, the word database is used for database systems or research and would apply to image database query techniques rather than a database containing images for use in specific applications. I have chosen to use dataset to describe collections of images used by researchers in some domain. In the past test data was difficult, but the advent of modern digital cameras has simplified acquiring data. But in order to test and especially compare algorithms, a common dataset is essential.

Test data is available in bits and pieces and in several larger repositories, These listed datasets are selected from the references in the Computer Vision Bibliography. There are other datasets and often older ones get removed from web sites. The links on the Author and Journal references in the list point to entries in that database. Current research and applications are highlighted in various Computer Vision and Image Processing Conferences. Some of these have evaluation sessions with related datasets.

Computer Vision resources include:

For more information on the topics, contact information, etc. see the annotated Computer Vision Bibliography or the Complete Conference Listing for Computer Vision and Image Analysis

Detailed Entries for Dataset

Khosla, A.[Aditya], Raju, A.S.[Akhil S.], Torralba, A.B.[Antonio B.], Oliva, A.[Aude],
Understanding and Predicting Image Memorability at a Large Scale,
Dataset, Memorability.
WWW Link. Benchmark testing

Barnard, K.[Kobus], and Funt, B.V.[Brian V.],
Camera characterization for color research,
ColorRes(27), No. 3, 2002, pp. 153-164.
PDF File. Dataset, Color Calibration.
WWW Link.

Huang, X.Y.[Xin-Yu], Wang, P.[Peng], Cheng, X.J.[Xin-Jing], Zhou, D.F.[Ding-Fu], Geng, Q.C.[Qi-Chuan], Yang, R.G.[Rui-Gang],
The ApolloScape Open Dataset for Autonomous Driving and Its Application,
PAMI(42), No. 10, October 2020, pp. 2702-2719.
Dataset, Autonomous Driving. Semantics, Task analysis, Videos, Labeling, Image segmentation, 3D understanding

DDD17: End-To-End DAVIS Driving Dataset,
WWW Link. Dataset, Road Scenes. Over 12 h of a 346x260 pixel DAVIS sensor recording highway and city driving in daytime, evening, night, dry and wet weather.

Waymo Open Dataset ,
WWW Link. Dataset, Road Scenes. high-resolution sensor data collected by autonomous vehicles operated by the Waymo Driver in a wide variety of situations.

Yu, F.[Fisher], Chen, H.F.[Hao-Feng], Wang, X.[Xin], Xian, W.Q.[Wen-Qi], Chen, Y.Y.[Ying-Ying], Liu, F.C.[Fang-Chen], Madhavan, V.[Vashisht], Darrell, T.J.[Trevor J.],
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning,
WWW Link. Dataset, Road Scenes. Task analysis, Visualization, Roads, Image segmentation, Meteorology, Training, Benchmark testing

UZH-FPV Drone Racing Dataset,
HTML Version. Dataset, Visual Odometry. 28 real-world sequences where a quadrotor controlled in first-person view.

See also Are We Ready for Autonomous Drone Racing? The UZH-FPV Drone Racing Dataset.

The ROad event Awareness Dataset for Autonomous Driving (ROAD),
WWW Link. Dataset, Autonomous Driving. It contains 22 long-duration videos (ca 8 minutes each), ideal for continual learning research, annotated in terms of road events, defined as triplets E = (Agent, Action, Location) and represented as tubes, i.e., a series of frame-wise bounding box detections. ROAD is a large, high-quality multi-label benchmark, with 122K labelled video frames comprising 560K detection bounding boxes associated with 1.7M unique individual labels (560K agent labels, 640K action labels and 499K location labels).

DSEC: A Stereo Event Camera Dataset for Driving Scenarios,
HTML Version. CVPR 2021 competition dataset. Dataset, Stereo. Dataset, Driving.
Stereo Event Camera large-scale dataset for challenging driving scenarios! DSEC features over 400GB of data including stereo VGA Prophesee event cameras, stereo RGB cameras, Velodyne lidar, and RTK-GPS, recorded in challenging high-dynamic-range, day and night, sunrise and sunset, urban and Swiss-mountain driving scenarios.

Yogamani, S., Hughes, C., Horgan, J., Sistu, G., Chennupati, S., Uricar, M., Milz, S., Simon, M., Amende, K., Witt, C., Rashed, H., Nayak, S., Mansoor, S., Varley, P., Perrotton, X., Odea, D., Pérez, P.,
WoodScape: A Multi-Task, Multi-Camera Fisheye Dataset for Autonomous Driving,
WWW Link.
Dataset, Autonomous Driving. automotive electronics, cameras, computer vision, driver information systems, image annotation, Nonlinear distortion

Zendel, O.[Oliver], Honauer, K.[Katrin], Murschitz, M.[Markus], Steininger, D.[Daniel], Domínguez, G.F.[Gustavo Fernández],
WildDash: Creating Hazard-Aware Benchmarks,
ECCV18(VI: 407-421).
Springer DOI
Dataset, Highway Hazards. Driving hazards.

Dev Roy, S., Kanti Bhowmik, M., Oakley, J.,
A Ground Truth Annotated Video Dataset for Moving Object Detection in Degraded Atmospheric Outdoor Scenes,
Dataset, Object Detection. Object detection, Lighting, Meteorology, Cameras, Image restoration, Streaming media, Atmospheric measurements, Image Enhancement

Codevilla, F., Santana, E., Lopez, A., Gaidon, A.,
Exploring the Limitations of Behavior Cloning for Autonomous Driving,
Dataset, Driver Behavior.
WWW Link. behavioural sciences computing, learning (artificial intelligence), neural nets, Vehicle dynamics

Lee, G.H.[Gim Hee], Achtelik, M., Fraundorfer, F., Pollefeys, M., Siegwart, R.,
A benchmarking tool for MAV visual pose estimation,
Dataset, SLAM. Large scale SLAM dataset with more sensors. For UAV algorithm evaluations.

Ji, R.R.[Rong-Rong], Duan, L.Y.[Ling-Yu], Chen, J.[Jie], Yang, S.[Shuang], Huang, T.J.[Tie-Jun], Yao, H.X.[Hong-Xun], Gao, W.[Wen],
PKUBench: A context rich mobile visual search benchmark,
Dataset, Landmarks. Landmark search aided by GPS.

Li, N.[Ning], Zhao, Y.Q.[Yong-Qiang], Pan, Q.[Quan], Kong, S.G.[Seong G.], Chan, J.C.W.[Jonathan Cheung-Wai],
Full-time Monocular Road Detection Using Zero-distribution Prior of Angle of Polarization,
Springer DOI
Dataset, Road Detection.
WWW Link.

Winkens, C., Sattler, F., Adams, V., Paulus, D.,
HyKo: A Spectral Dataset for Scene Understanding,
Dataset, Roads. Autonomous vehicles, Cameras, Hypercubes, Hyperspectral imaging, Image color analysis, Sensors

Schmidt, A.[Adam], Fularz, M.[Michal], Kraft, M.[Marek], Kasinski, A.[Andrzej], Nowicki, M.[Michal],
An Indoor RGB-D Dataset for the Evaluation of Robot Navigation Algorithms,
Springer DOI
Dataset, Navigation.

Swedish Trafic Signs,
WWW Link. Dataset, Traffic Signs.

Challenging Unreal and Real Environments for Traffic Sign Detection and Recognition,
Online2017 CURE-TSD and CURE-TSR
WWW Link.
WWW Link. Dataset, Traffic Signs. Dataset, CURE-TSR. Dataset, CURE-TSD. Real-world and synthesized video sequences with challenging conditions. In total, there are 5,733 video sequences and around 1.72 million frames.

CMU VASC Image Database,
WWW Link. Dataset, Motion. CMU has a collection of image datasets available. These include a number of motion sequences, stereo (with and without ground truth), faces and expressions, and cars.

PEIPA Computer Vision Software,
HTML Version. Code, Computer Vision. Dataset. Pilot European Image Processing Archive. This lists a number of sources for various alogrithms. They also include pointers to the usual set of image databases.

BBC Motion Gallery,
Video data. Online2004
WWW Link. Video clips, including rights managed and production ready royalty-free footage. Available to preview, purchase and download. Dataset, Retrieval. Dataset, Video.

Large Scale Dataset for Cross-Model Multimedia Analysis,
HTML Version. Dataset, Image Retrieval. Dataset, Text Retrieval.
See also Large Scale Video Database.

Shirahatti, N.V.[Nikhil V.], Barnard, K.[Kobus],
Evaluating Image Retrieval,
CVPR05(I: 955-961).
HTML Version.
Code, Image Retrieval. Dataset, Image Retrieval.

Duygulu, P., Barnard, K., de Freitas, J.F.G., Forsyth, D.A.,
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary,
ECCV02(IV: 97 ff.). Award, ECCV, Cognitive Vision.
Springer DOI
HTML Version.
Dataset, Object Recognition.

Murray, N.[Naila], Marchesotti, L.[Luca], Perronnin, F.[Florent],
Learning to rank images using semantic and aesthetic labels,
DOI Link

AVA: A large-scale database for aesthetic visual analysis,
Dataset, Aesthetic Analysis.

Visual7W visual question answering,
Large-scale visual question answering (QA) dataset, with object-level groundings and multimodal answers. WWW Link.
Dataset, Visual Question Answering.

Visual Genome,
Visual Genome is a dataset, a knowledge base, an ongoing effort to connect structured image concepts to language. WWW Link.

WWW Link. Dataset, Visual Question Answering.

Mathew, M.[Minesh], Karatzas, D.[Dimosthenis], Jawahar, C.V.,
DocVQA: A Dataset for VQA on Document Images,
WWW Link.
Dataset, Visual Q-A. Visualization, Text analysis, Image recognition, Image analysis, Layout

Johnson, J.[Justin], Hariharan, B.[Bharath], van der Maaten, L.[Laurens], Hoffman, J., Fei-Fei, L.[Li], Zitnick, C.L.[C. Lawrence], Girshick, R.[Ross],
Inferring and Executing Programs for Visual Reasoning,

Earlier: A1, A2, A3, A5, A6, A7, Only:
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning,
Dataset, Visual Reasoning.
WWW Link. backpropagation, image matching, learning (artificial intelligence), neural nets, Visualization. Cognition, Image color analysis, Metals, Semantics, Shape.

UT Zappos50K,
Dataset, Shoes.
WWW Link.
University of Texas shoe dataset. 50,025 images.

Xiao, J.X.[Jian-Xiong], Hays, J.[James], Ehinger, K.A.[Krista A.], Oliva, A.[Aude], Torralba, A.B.[Antonio B.],
SUN database: Large-scale scene recognition from abbey to zoo,
JEP:HPP(36), No. 6, 2010, pp. 1430-1442.
And: CVPR10(3485-3492).
Dataset, Recognition.
WWW Link. 131067 images, 908 categories, objects and object categories.

Xiao, J.X.[Jian-Xiong], Ehinger, K.A.[Krista A.], Hays, J.[James], Torralba, A.[Antonio], Oliva, A.[Aude],
SUN Database: Exploring a Large Collection of Scene Categories,
IJCV(119), No. 1, August 2016, pp. 3-22.
Springer DOI
Dataset, Object Recognition.
WWW Link.

Le Cun, Y.L.[Yann L.], Huang, F.J.[Fu Jie], Bottou, L.[Leon],
Learning methods for generic object recognition with invariance to pose and lighting,
CVPR04(II: 97-104).
PDF File.
WWW Link.
Dataset, Objects. Real time implementation. Find generic objects.

Blandfort, P.[Philipp], Karayil, T.[Tushar], Hees, J.[Jörn], Dengel, A.[Andreas],
The Focus-Aspect-Value model for predicting subjective visual attributes,
MultInfoRetr(9), No. 1, March 2020, pp. 47-60.
Springer DOI
Dataset, Retrieval.
WWW Link.

Philbin, J.[James], Chum, O.[Ondrej], Isard, M.[Michael], Sivic, J.[Josef], Zisserman, A.[Andrew],
Lost in quantization: Improving particular object retrieval in large scale image databases,
HTML Version.
Dataset, Objects.

Chum, O.[Ondrej], Philbin, J.[James], Sivic, J.[Josef], Isard, M.[Michael], Zisserman, A.[Andrew],
Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval,

And: A2, A1, A4, A3, A5:
Object retrieval with large vocabularies and fast spatial matching,
HTML Version.
Dataset, Buildings. Award, Longuet-Higgins. (after 10 years).

Bell, S.[Sean], Upchurch, P.[Paul], Snavely, N.[Noah], Bala, K.[Kavita],
Material recognition in the wild with the Materials in Context Database,

MINC Dataset,
WWW Link. Dataset, Materials.

Large Scale Video Database,
WWW Link. Dataset, Video Database.
This database consists of 156,823 videos sequences (2,907,447 keyframes), which were crawled from YouTube during the period of July 2010 to September 2010. We provide the features as well as the ground truth.
See also Multiple feature hashing for real-time large scale near-duplicate video retrieval.
See also Large Scale Dataset for Cross-Model Multimedia Analysis.

MA14KD: Movie Attraction 14K Dataset,

WWW Link. Dataset, Visual Attractiveness. MA14KD provides a set of "Attractiveness" features extracted from 14000 movie and TV series trailers. The movie IDs are in agreement with the movie IDs provided by a rating dataset, that contains millions of ratings and thousands of tags.

Xu, J.[Jun], Mei, T.[Tao], Yao, T.[Ting], Rui, Y.[Yong],
MSR-VTT: A Large Video Description Dataset for Bridging Video and Language,
Dataset, Video Analysis.
See also MSR VTT Dataset.

Li, Y.C.[Yun-Cheng], Song, Y.[Yale], Cao, L.L.[Liang-Liang], Tetreault, J.[Joel], Goldberg, L.[Larry], Jaimes, A.[Alejandro], Luo, J.B.[Jie-Bo],
TGIF: A New Dataset and Benchmark on Animated GIF Description,
WWW Link. Dataset, Animations.

Liu, J.Z.[Jing-Zhou], Chen, W.[Wenhu], Cheng, Y.[Yu], Gan, Z.[Zhe], Yu, L.C.[Li-Cheng], Yang, Y.M.[Yi-Ming], Liu, J.J.[Jing-Jing],
Violin: A Large-Scale Dataset for Video-and-Language Inference,
Dataset, Video. Task analysis, Visualization, Cognition, Natural languages, TV, Motion pictures, Benchmark testing

Huang, Q.Q.[Qing-Qiu], Xiong, Y.[Yu], Rao, A.[Anyi], Wang, J.Z.[Jia-Ze], Lin, D.H.[Da-Hua],
Movienet: A Holistic Dataset for Movie Understanding,
Springer DOI
Dataset, Movie Understanding.
WWW Link.

Deep Video Understanding Dataset,
2020, used for workshops, and challenges. WWW Link.
Dataset, Video Understanding.

Bakker, E.M.[Erwin M.],
Open and free datasets for multimedia retrieval,
MultInfoRetr(5), No. 3, September 2016, pp. 135-136.
WWW Link.
Dataset, Multimedia Retrieval.

Animals with Attributes 2 Dataset,
2017 Dataset, Animals.
WWW Link. Reference:
See also Zero-Shot Learning: The Good, the Bad and the Ugly. Note the earlier AWA dataset has been removed due to copyright issues and replaces with this version.

Swanson, A.[Alexandra], Kosmala, M.[Margaret], Lintott, C.[Chris], Simpson, R.[Robert], Smith, A.[Arfon], Packer, C.[Craig],
Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna,
ScientificData(2), June 2015, Article 150026.
DOI Link
Dataset, Animals. Covered by many news outlets. Thousands of pictures of animals from motion activated cameras planted in the Serengeti. Includes interface for people to identify, etc. A great resource for automated detection and identification.

Nilsback, M.E.[Maria-Elena], Zisserman, A.[Andrew],
Automated Flower Classification over a Large Number of Classes,
HTML Version. Dataset, Flowers.
HTML Version.

Plant Phenotyping Datasets for Computer Vision,
WWW Link. Dataset, Plants. We present a collection of benchmark datasets in the context of plant phenotyping. We provide annotated imaging data and suggest suitable evaluation criteria for plant/leaf segmentation, detection, tracking as well as classification and regression problems. The figure symbolically depicts the data available together with ground truth segmentations and further annotations and metadata. Article in press.
See also Finely-grained annotated datasets for image-based plant phenotyping.

Wood image database,
WWW Link.
WWW Link. For information also see:
HTML Version. Dataset, Lumber.

Beery, S.[Sara], van Horn, G.[Grant], Perona, P.[Pietro],
Recognition in Terra Incognita,
ECCV18(XVI: 472-489).
Springer DOI
Dataset, Animals.
WWW Link.

Tropical Coral Reef Fish Detection, Tracking And Classification,
Fish4Knowledge project datasets. Online2014
WWW Link. Dataset, Fish.
See also University of Edinburgh.
See also Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data.

Pre-Corrective Optics Space Telescope Axial Replacement Hubble Space Telescope star-cluster dataset,
Astronomy dataset. Dataset, Astronomy.
WWW Link.

Ramanathan, S.[Subramanian], Katti, H.[Harish], Sebe, N.[Nicu], Kankanhalli, M.[Mohan], Chua, T.S.[Tat-Seng],
An Eye Fixation Database for Saliency Detection in Images,
ECCV10(IV: 30-43).
Springer DOI
Dataset, Eye Fixation.

Rivera-Rubio, J.[Jose], Idrees, S.[Saad], Alexiou, I.[Ioannis], Hadjilucas, L.[Lucas], Bharath, A.A.[Anil A.],
A dataset for Hand-Held Object Recognition,
Dataset, Object Recognition.
Small Hand-Held Object Recognition Test (SHORT),

Mobile Visual Assistive Apps: Benchmarks of Vision Algorithm Performance,
Springer DOI
Computer vision Cameras

2020. Research Group, Europe.
WWW Link. Accelerating Geospatial Machine Learning Dataset, Mapping.
WWW Link.

Koch, T.[Tobias], d'Angelo, P.[Pablo], Kurz, F.[Franz], Fraundorfer, F.[Friedrich], Reinartz, P.[Peter], Körner, M.[Marco],
The TUM-DLR Multimodal Earth Observation Evaluation Benchmark,
Dataset, Remote Sensing.
WWW Link. Same scene, satellite, air, UAV, smartphone.

Shermeyer, J., Hogan, D., Brown, J., van Etten, A., Weir, N., Pacifici, F., Hänsch, R., Bastidas, A., Soenen, S., Bacastow, T., Lewis, R.,
SpaceNet 6: Multi-Sensor All Weather Mapping Dataset,
Dataset, Mapping. Synthetic aperture radar, Optical sensors, Optical imaging, Adaptive optics, Optical polarization, Buildings

Zhou, D.B.[Dong-Bo], Liu, S.[Shuangjian], Yu, J.[Jie], Li, H.[Hao],
A High-Resolution Spatial and Time-Series Labeled Unmanned Aerial Vehicle Image Dataset for Middle-Season Rice,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link
Dataset, Rice.

Tan, W., Qin, N., Ma, L., Li, Y., Du, J., Cai, G., Yang, K., Li, J.,
Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways,
Dataset, LiDAR. Semantics, Roads, Laser radar, Sensors, Machine learning, Automobiles

Hudson, W.H., Nadadur, D.C., Thornton, K.B., Liu, X., Haralick, R.M.,
The Radius CDROM Ground Truthed Data Set,
ARPA96(511-519). Dataset. Ground truth buildings for other users.

ISPRS benchmark on urban object detection and 3D building reconstruction,
HTML Version. Dataset, Building Detection. Provide state-of-the-art data sets which can be used by interested researchers in order to test own methods and algorithms on urban object classification and building reconstruction.

Teller, S.[Seth], Antone, M.[Matthew], Bodnar, Z.[Zachary], Bosse, M.[Michael], Coorg, S.[Satyan], Jethwa, M.[Manish], Master, N.[Neel],
Calibrated, Registered Images of an Extended Urban Area,
IJCV(53), No. 1, June 2003, pp. 93-107.
DOI Link
Dataset, Buildings.
Earlier: CVPR01(I:813-820).
More the dataset than how to analyze the data.
WWW Link.
See also Spherical Mosaics with Quaternions and Dense Correlation.

Meinel, G.[Gotthard], Burckhardt, M.[Manuel],
The Digital Basic Geodata Sets Hausumringe and Hauskoordinaten: Characterization and Pre-processing for Building Stock Analysis,
PFG(2013), No. 6, 2013, pp. 575-588.
DOI Link
Dataset, Buildings.

ISPRS Test Project on Urban Classification and 3D Building Reconstruction,
LIDAR data for building descrtiptions.
WWW Link. Dataset, Building Extraction. Used for ISPRS 3D Labeling contest.

Ye, Z.[Zhen], Xu, Y.S.[Yu-Sheng], Huang, R.[Rong], Tong, X.H.[Xiao-Hua], Li, X.[Xin], Liu, X.F.[Xiang-Feng], Luan, K.F.[Kui-Feng], Hoegner, L.[Ludwig], Stilla, U.[Uwe],
LASDU: A Large-Scale Aerial LiDAR Dataset for Semantic Labeling in Dense Urban Areas,
IJGI(9), No. 7, 2020, pp. xx-yy.
DOI Link
Dataset, LiDAR.

NYU Depth Dataset V2,
HTML Version. Dataset, RGBD. Dataset, Indoor Scenes.
See also Indoor Segmentation and Support Inference from RGBD Images.

Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., Franke, U., Roth, S., Schiele, B.,
The Cityscapes Dataset for Semantic Urban Scene Understanding,
WWW Link.
WWW Link.
WWW Link.
WWW Link.
Dataset, City Models.

Ros, G., Sellart, L., Materzynska, J., Vazquez, D., Lopez, A.M.,
The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes,
Dataset, City Models.

Ma, Y.C.[Yan-Chun], Liu, Y.J.[Yong-Jian], Xie, Q.[Qing], Xiong, S.W.[Sheng-Wu], Bai, L.H.[Li-Hua], Hu, A.[Anshu],
A Tibetan Thangka data set and relative tasks,
IVC(108), 2021, pp. 104125.
Elsevier DOI
Dataset, Tibetan Culture. Chomo Yarlung Tibet version 1. Image data set, Thangka data set, Tibetan culture, Semantic content analysis, Image processing

3-D, Laser data collection and archiving.
WWW Link. Vendor, Cultural Heritage. Dataset, Cultural Heritage. Digiatal Archive of the world's heritage sites for preservation and education. Not a vendor as such, but an archive and group that will collect the data. Some are small, some huge. Used for sites being destroyed, or for reconstruction. Visualizations, etc.

Weir, N., Lindenbaum, D., Bastidas, A., Etten, A., Kumar, V., Mcpherson, S., Shermeyer, J., Tang, H.,
SpaceNet MVOI: A Multi-View Overhead Imagery Dataset,
Dataset, Stereo. computer vision, feature extraction, image classification, image colour analysis, image resolution, image segmentation, Computer vision

WWW Link. Dataset, Surveillance.

Earlier: UCF Aerial Action Dataset,
WWW Link. A:Aerial Camera, R: Roof top camera, G: Ground camera. 3 views of different actions. The aerial subset

DOTA: A Large-Scale Benchmark and Challenges for Object Detection in Aerial Images,
WWW Link. Dataset, Aerial Objects.
2806 aerial images obtained from different sensors and platforms, including 15 classification categories (vehicle, track, storange tanks, sports fields, etc.)

TGRS-HRRSD-Dataset: High Resolution Remote Sensing Detection (HRRSD),
WWW Link. Dataset, Aerial Objects.
21,761 images. in 13 categories.
See also Hierarchical and Robust Convolutional Neural Network for Very High-Resolution Remote Sensing Object Detection.

Jha, S.S.[Sudhanshu Shekhar], Nidamanuri, R.R.[Rama Rao],
Gudalur Spectral Target Detection (GST-D): A New Benchmark Dataset and Engineered Material Target Detection in Multi-Platform Remote Sensing Data,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link
Dataset, Targets. Target detection, or sparsely distributed materials.

Xia, G.S.[Gui-Song], Bai, X.[Xiang], Ding, J.[Jian], Zhu, Z.[Zhen], Belongie, S.[Serge], Luo, J.[Jiebo], Datcu, M.[Mihai], Pelillo, M.[Marcello], Zhang, L.P.[Liang-Pei],
DOTA: A Large-Scale Dataset for Object Detection in Aerial Images,
Dataset, Vehicle Detection.
WWW Link. Object detection, Earth, Sports, Computer vision, Sensors, Marine vehicles, Image sensors

Matzen, K.[Kevin], Snavely, N.[Noah],
NYC3DCars: A Dataset of 3D Vehicles in Geographic Context,
Dataset, Vehicles. 3D models; geography; object detection; structure from motion

Boat Detection,
HTML Version. Dataset, Ships.
WWW Link. Public video dataset for boat detection/tracking from UAV video footage
See also Racing Bicycle Detection/Tracking from UAV Footage, UAV Detection.

Di, Y.H.[Yang-Hua], Jiang, Z.G.[Zhi-Guo], Zhang, H.[Haopeng],
A Public Dataset for Fine-Grained Ship Classification in Optical Remote Sensing Images,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
Dataset, Ships.

Liu, Z.Y.[Zhao-Ying], Waqas, M.[Muhammad], Yang, J.[Jia], Rashid, A.[Ahmar], Han, Z.[Zhu],
A Multi-Task CNN for Maritime Target Detection,
SPLetters(28), 2021, pp. 434-438.
Dataset, Ship Detection. MaRine ShiP (MRSP-13) Dataset. Marine vehicles, Task analysis, Object detection, Image segmentation, Boats, Feature extraction, Annotations, cross-layer connections

Gundogdu, E.[Erhan], Solmaz, B.[Berkan], Yücesoy, V.[Veysel], Koç, A.[Aykut],
MARVEL: A Large-Scale Image Dataset for Maritime Vessels,
ACCV16(V: 165-180).
Springer DOI
Dataset, Ships.

Mostajabi, M.[Mohammadreza], Wang, C.M.[Ching Ming], Ranjan, D.[Darsh], Hsyu, G.[Gilbert],
High Resolution Radar Dataset for Semi-Supervised Learning of Dynamic Objects,
Dataset, Radar. Synthetic aperture radar, Radar imaging, Spaceborne radar, Image resolution, Apertures, Azimuth

Japanese Character Image Database,
Cedar (Buffalo) database. Dataset, OCR.
WWW Link. Test data for Japanese OCR.

Wang, D.H.[Da-Han], Liu, C.L.[Cheng-Lin], Yu, J.L.[Jin-Lun], Zhou, X.D.[Xiang-Dong],
CASIA-OLHWDB1: A Database of Online Handwritten Chinese Characters,
Dataset, OCR.

Zhou, S.[Shusen], Chen, Q.C.[Qing-Cai], Wang, X.L.[Xiao-Long], Guo, X.[Xinyi], Li, H.[Hui],
An Empirical Evaluation on HIT-OR3C Database,
Dataset, OCR. Handwriting Chinese character database (HIT-OR3C)

Yan, H.[Hanyu], Jin, L.W.[Lian-Wen], Viard-Gaudin, C.[Christian], Mouchere, H.[Harold],
SCUT-COUCH Textline_NU: An Unconstrained Online Handwritten Chinese Text Lines Dataset,
Dataset, Chinese Characters.

Zhang, H.G.[Hong-Gang], Guo, J.[Jun], Chen, G.[Guang], Li, C.G.[Chun-Guang],
HCL2000: A Large-scale Handwritten Chinese Character Database for Handwritten Character Recognition,
Dataset, OCR.

Liu, C.L.[Cheng-Lin], Yin, F.[Fei], Wang, D.H.[Da-Han], Wang, Q.F.[Qiu-Feng],
Online and offline handwritten Chinese character recognition: Benchmarking on new databases,
PR(46), No. 1, January 2013, pp. 155-162.
Elsevier DOI

CASIA Online and Offline Chinese Handwriting Databases,
Dataset, OCR. Handwritten Chinese character recognition; Online; Offline; Databases; Benchmarking
See also Touching Character Database from Chinese Handwriting for Assessing Segmentation Algorithms, A.

Hull, J.J.,
A Database for Handwritten Text Recognition Research,
PAMI(16), No. 5, May 1994, pp. 550-554.
IEEE DOI Dataset, Handwriting. Handwriting Database.

Ground Truthed Handwritten Word Images,
Cambridge University dataset. Dataset, Handwriting.
HTML Version.

On-line Handwriting Database,
Tokyo Univ. of Agri. & Tech., Nakagawa Laboratory. Dataset, Handwriting.
WWW Link.

Shivram, A., Ramaiah, C., Setlur, S., Govindaraju, V.,
IBM_UB_1: A Dual Mode Unconstrained English Handwriting Dataset,
Dataset, OCR. handwriting recognition

Ben Abdelghani, I.A.[Imen Abroug], Ben Amara, N.E.[Najoua Essoukri],
SID Signature Database: A Tunisian Off-line Handwritten Signature Database,
Springer DOI
Dataset, Signatures.

Kleber, F., Fiel, S., Diem, M., Sablatnig, R.,
CVL-DataBase: An Off-Line Database for Writer Retrieval, Writer Identification and Word Spotting,
Dataset, Writer Identification. XML

The Street View House Numbers (SVHN) Dataset ,
2011 WWW Link.
Dataset, House Numbers. 600,000 digit images.

USPS Office of Advanced Technology Database of Handwritten Cities, States, ZIP Codes, Digits, and Alphabetic Characters,
Cedar (Buffalo) database. Dataset, Handwriting.
WWW Link. Database for mail processing.

Dimauro, G., Impedovo, S., Modugno, R., Pirlo, G.,
A new database for research on bank-check processing,
IEEE Top Reference.
Dataset, Checks.

Ma, L.L., Liu, J.[Ji], Wu, J.,
A new database for online handwritten Mongolian word recognition,
Dataset, Mongolian Characters. Character recognition, Databases, Handwriting recognition, Layout, Sampling methods, Training, Writing, CNN, MRG-OHMW, annotation, evaluation, online, handwritten, Mongolian, word, recognition

Ali, H.[Hazrat],
UHaT: Urdu handwritten text dataset,
WWW Link. Dataset, Urdu. Urdu handwritten characters and digits.

Das, N.[Nibaran], Acharya, K.[Kallol], Sarkar, R.[Ram], Basu, S.[Subhadip], Kundu, M.[Mahantapas], Nasipuri, M.[Mita],
A benchmark image database of isolated Bangla handwritten compound characters,
IJDAR(17), No. 4, December 2014, pp. 413-431.
Springer DOI
WWW Link.
Dataset, Bangla.

Sarkar, R.[Ram], Das, N.[Nibaran], Basu, S.[Subhadip], Kundu, M.[Mahantapas], Nasipuri, M.[Mita], Basu, D.K.[Dipak Kumar],
CMATERdb1: A database of unconstrained handwritten Bangla and Bangla-English mixed script document image,
IJDAR(15), No. 1, March 2012, pp. 71-83.
WWW Link.
Dataset, Bangla.

Nethravathi, B., Archana, C.P., Shashikiran, K., Ramakrishnan, A.G., Kumar, V.[Vijay],
Creation of a Huge Annotated Database for Tamil and Kannada OHR,
Dataset, OCR.

Sagheer, M.W.[Malik Waqas], He, C.L.[Chun Lei], Nobile, N.[Nicola], Suen, C.Y.[Ching Y.],
A New Large Urdu Database for Off-Line Handwriting Recognition,
Springer DOI
Dataset, Urdu Handwriting.

ERIM Arabic Document Database,
Machine printed Arabic documents. Dataset, OCR. Dataset, Arabic.
HTML Version.

Mahmoud, S.A.[Sabri A.], Ahmad, I.[Irfan], Al-Khatib, W.G.[Wasfi G.], Alshayeb, M.[Mohammad], Parvez, M.T.[Mohammad Tanvir], Märgner, V.[Volker], Fink, G.A.[Gernot A.],
KHATT: An open Arabic offline handwritten text database,
PR(47), No. 3, 2014, pp. 1096-1112.
Elsevier DOI
Dataset, Arabic Text. Arabic handwritten text database

Mahmoud, S.A.[Sabri A.], Ahmad, I.[Irfan], Alshayeb, M.[Mohammad], Al-Khatib, W.G.[Wasfi G.], Parvez, M.T.[Mohammad Tanvir], Fink, G.A.[Gernot A.], Margner, V.[Volker], El Abed, H.[Haikal],
KHATT: Arabic Offline Handwritten Text Database,
Dataset, Handwritting, Arabic.

Lamghari, N.[Nidal], Raghay, S.[Said],
DBAHCL: database for Arabic handwritten characters and ligatures,
MultInfoRetr(6), No. 3, September 2017, pp. 263-269.
Springer DOI
Dataset, Arabic Characters.

Al Maadeed, S.[Somaya], Ayouby, W.[Wael], Hassaine, A.[Abdelaali], Aljaam, J.M.[Jihad Mohamad],
QUWI: An Arabic and English Handwriting Dataset for Offline Writer Identification,
Dataset, Arabic.

Soleimani, A., Fouladi, K., Araabi, B.N.,
UTSig: A Persian offline signature dataset,
IET-Bio(6), No. 1, 2017, pp. 1-8.
DOI Link
Dataset, Persian. handwriting recognition

Ziaratban, M.[Majid], Faez, K.[Karim], Bagheri, F.[Fatemeh],
FHT: An Unconstraint Farsi Handwritten Text Database,
Dataset, OCR.

Haghighi, P.J.[Puntis Jifroodian], Nobile, N.[Nicola], He, C.L.[Chun Lei], Suen, C.Y.[Ching Y.],
A New Large-Scale Multi-purpose Handwritten Farsi Database,
Springer DOI
Dataset, Farsi Handwriting.

NIST OCR Databases,
WWW Link. Dataset, OCR. Dataset, Documents. A series of datasets for OCR and document analysis.

Sauvola, J., Kauniskangas, H.,
Media Team Document Database II,
WWW Link. Dataset, Document Analysis.

Todoran, L.[Leon], Worring, M.[Marcel], Smeulders, A.W.M.[Arnold W. M.],
The UvA color document dataset,
IJDAR(7), No. 4, September 2005, pp. 228-240.
Springer DOI
Dataset, Documents.
Data GroundTruth, Complexity, and Evaluation Measures for Color Document Analysis,
DAS02(519 ff.).
Springer DOI

Bukhari, S.S.[Syed Saqib], Shafait, F.[Faisal], Breuel, T.M.[Thomas M.],
The IUPR Dataset of Camera-Captured Document Images,
Springer DOI
Dataset, Document Images.

Nagy, R.[Robert], Dicker, A.[Anders], Meyer-Wegener, K.[Klaus],
NEOCR: A Configurable Dataset for Natural Image Text Recognition,
Springer DOI
Dataset, Natural Image Text.

Ibrahim, A.[Ahmed], Abbott, A.L.[A. Lynn], Hussein, M.E.[Mohamed E.],
An Image Dataset of Text Patches in Everyday Scenes,
ISVC16(II: 291-300).
Springer DOI
Dataset, Scene Text.

Ikica, A.[Andrej], Peer, P.[Peter],
Computer Vision Lab OCR DataBase: CVL OCR DB,
2011. A public annotated image database of text in natural scenes
WWW Link. Dataset, Text in Images.

Guerin, C., Rigaud, C., Mercier, A., Ammar-Boudjelal, F., Bertet, K., Bouju, A., Burie, J.C., Louis, G., Ogier, J.M., Revel, A.,
eBDtheque: A Representative Database of Comics,
Dataset, Comics. entertainment

Quiniou, S.[Solen], Mouchere, H.[Harold], Saldarriaga, S.P.[Sebastián Pen], Viard-Gaudin, C.[Christian], Morin, E.[Emmanuel], Petitrenaud, S.[Simon], Medjkoune, S.[Sofiane],
HAMEX: A Handwritten and Audio Dataset of Mathematical Expressions,
Dataset, OCR.

Stria, J.[Jan], Bresler, M.[Martin], Prua, D.[Daniel], Hlavác, V.[Vaclav],
MfrDB: Database of Annotated On-Line Mathematical Formulae,
Dataset, Formula.

WWW Link. Dataset, Logos. 32 logo classes, various orientations, surface shapes, etc.

UMD Logo Database,
Univ. Maryland database of 106 corportate logos. Dataset, Logos.
HTML Version.

Yang, Z.L.[Zhong-Liang], Wang, K.[Ke], Ma, S.[Sai], Huang, Y.F.[Yong-Feng], Kang, X.G.[Xian-Gui], Zhao, X.F.[Xian-Feng],
ISTEGO100K: Large-scale Image Steganalysis Dataset,
Springer DOI
Dataset, Setganalysis.

Rocha, A.[Anderson], Goldenstein, S.K.[Siome K.], Scheirer, W.J.[Walter J.], Boult, T.E.[Terrance E.],
The Unseen Challenge data sets,
Dataset, Steganalysis.

Unipen Project,
Online1994. Dataset, Handwriting.
WWW Link. This is a working group organized through IAPR to maintain and protect (ensure available to researchers) various databases of handwriting data.

Njah, S.[Sourour], Ben Nouma, B.[Badreddine], Bezine, H.[Hala], Alimi, A.M.[Adel M.],
MAYASTROUN: A Multilanguage Handwriting Database,
Dataset, Handwriting.

Pérez, D.[Daniel], Tarazón, L.[Lionel], Serrano, N.[Nicolás], Castro, F.[Francisco], Terrades, O.R.[Oriol Ramos], Juan, A.[Alfons],
The GERMANA Database,
Dataset, OCR. Handwritten Spanish manuscript from 1891.

Aytekin, Ç., Nikkanen, J., Gabbouj, M.,
A Data Set for Camera-Independent Color Constancy,
IP(27), No. 2, February 2018, pp. 530-544.
Dataset, Color Constancy. Cameras, Image color analysis, Lighting, Reflectivity, Robustness, Sensitivity, Training, Color constancy, color shading, platform independence

Barnard, K.[Kobus], Martin, L.[Lindsay], Funt, B.V.[Brian V.], and Coath, A.[Adam],
A Data Set for Colour Research,
ColorRes(27), No 3, 2002, pp. 147-151.
HTML Version. Dataset, Color Constancy.
HTML Version.

Soundararajan, P.[Padmanabhan], Sarkar, S.[Sudeep],
An in-depth study of graph partitioning measures for perceptual organization,
PAMI(25), No. 6, June 2003, pp. 642-660.
IEEE Abstract.
Evaluation, Segmentation.
WWW Link. Code, Perceptual Grouping. Dataset, Perceptual Grouping.
Empirical evaluation of graph partitioning measures for perceptual organization,
Quality of groups generated by minimum (
See also Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image Segmentation, An. ) or average (
See also Supervised Learning of Large Perceptual Organization: Graph Spectral Partitioning and Learning Automata. ) or normalized (
See also Normalized Cuts and Image Segmentation. ) cuts are equivalent for recognition.

Wang, T.C.[Ting-Chun], Zhu, J.Y.[Jun-Yan], Hiroaki, E.[Ebi], Chandraker, M.[Manmohan], Efros, A.A.[Alexei A.], Ramamoorthi, R.[Ravi],
A 4D Light-Field Dataset and CNN Architectures for Material Recognition,
ECCV16(III: 121-138).
Springer DOI
Dataset, Material Recognition.

Large Geometric Models Archive,
WWW Link. Dataset, 3-D Models. Detailed 3-D models from Georgia Institute of Technology. Especially for graphics.
See also Georgia Tech.

Digne, J.[Julie], Audfray, N.[Nicolas], Lartigue, C.[Claire], Mehdi-Souzani, C.[Charyar], Morel, J.M.[Jean-Michel],
Farman Institute 3D Point Sets: High Precision 3D Data Sets,
IPOL(2011), No. 1, 2011, pp. xx-yy.
DOI Link
Dataset, 3D Data.

ISPRS Terrestrial laser scanning and 3D imaging Datasets,
HTML Version. Dataset, 3-D Data. 3-D datasets for large scale objects. Sanmarina Byzantine church and Golden Buddha.

NaturePix: Visual Cognitive Modeling Research,
WWW Link. Dataset, 3-D Data. ASU 3-D datasets. Replaces former ASU dataset?

The Stanford 3D Scanning Repository,
WWW Link. Dataset, 3-D Data. Stanford graphics databases

The Beazley Archive of Classical Art Pottery Database,
July 2013
WWW Link. Dataset, Pottery.

Oliva, A.[Aude], Torralba, A.B.[Antonio B.],
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope,
IJCV(42), No. 3, May-June 2001, pp. 145-175.
DOI Link
WWW Link.
Dataset, Outdoor Secens.
Scene-Centered Description from Spatial Envelope Properties,
BMCV02(263 ff.).
Springer DOI
Otherwise known as OSR dataset. Spatial envelope: low dimensional representation of the secen. Perceptual dimensions to represent the dominat satial structure.

Patro, B.N.[Badri N.], Lunayach, M.[Mayank], Srivastava, D.[Deepankar], Sarvesh, S.[Sarvesh], Singh, H.[Hunar], Namboodiri, V.P.[Vinay P.],
Multimodal Humor Dataset: Predicting Laughter tracks for Sitcoms,
WWW Link.
Dataset, Humor. Annotations, Semantics, Bit error rate, Manuals, Task analysis

Uy, M.A., Pham, Q., Hua, B., Nguyen, T., Yeung, S.,
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data,
Dataset, Point Cloud.
WWW Link. CAD, feature extraction, learning (artificial intelligence), neural nets, Market research

Hodan, T.[Tomáš], Haluza, P.[Pavel], Obdržálek, Š.[Štepán], Matas, J.G.[Jirí G.], Lourakis, M.[Manolis], Zabulis, X.[Xenophon],
T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-Less Objects,
Dataset, RBG-D.
WWW Link. (Slow response) Image color analysis, Image sensors, Pose estimation, Sensors, Solid modeling, Training

Bellmann, A.[Anke], Hellwich, O.[Olaf], Rodehorst, V.[Volker], Yilmaz, U.[Ulas],
A Benchmarking Dataset for Performance Evaluation of Automatic Surface Reconstruction Algorithms,
Dataset, Surface Reconstruction.

Lee, S.K.[Seung-Kyu], Liu, Y.X.[Yan-Xi],
Curved Glide-Reflection Symmetry Detection,
PAMI(34), No. 2, February 2012, pp. 266-278.

Earlier: CVPR09(1046-1053).
Generalize Bilateral reflection symmetry to curved glide-reflection. Leaf images. Dataset, Symmetry Images.

Alpha Matting Evaluation Website,
WWW Link. Dataset, Image Matting.
See also perceptually motivated online benchmark for image matting, A.

How2 Dataset,
WWW Link. Instructional videos Used in How2 Challenge at ICML 2009 Dataset, Instructional Video.

WWW Link. Cooking videos Dataset, Instructional Video.

Alayrac, J.B.[Jean-Baptiste], Bojanowski, P.[Piotr], Agrawal, N.[Nishant], Sivic, J.[Josef], Laptev, I.[Ivan], Lacoste-Julien, S.[Simon],
Learning from Narrated Instruction Videos,
PAMI(40), No. 9, September 2018, pp. 2194-2208.
Dataset, Instructional Video.
WWW Link.
Unsupervised Learning from Narrated Instruction Videos,
Videos, Automobiles, Visualization, Tires, YouTube, Internet, Pragmatics, Step discovery, narrated instruction videos, unsupervised learning. Text and images from video for learning the steps.

Miech, A., Zhukov, D., Alayrac, J., Tapaswi, M., Laptev, I., Sivic, J.,
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips,
WWW Link. Dataset, Instructional Video. Internet, learning (artificial intelligence), natural language processing, social networking (online), Computational modeling

Zhukov, D.[Dimitri], Alayrac, J.B.[Jean-Baptiste], Cinbis, R.G.[Ramazan Gokberk], Fouhey, D.[David], Laptev, I.[Ivan], Sivic, J.[Josef],
Cross-Task Weakly Supervised Learning From Instructional Videos,
Dataset, Instructional Video.
WWW Link.

Tang, Y.S.[Yan-Song], Ding, D.J.[Da-Jun], Rao, Y.M.[Yong-Ming], Zheng, Y.[Yu], Zhang, D.Y.[Dan-Yang], Zhao, L.[Lili], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
COIN: A Large-Scale Dataset for Comprehensive Instructional Video Analysis,
Dataset, Instructional Video.
WWW Link.

Vidal, R.G.[Rosaura G.], Banerjee, S.[Sreya], Grm, K.[Klemen], Struc, V.[Vitomir], Scheirer, W.J.[Walter J.],
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition,

WWW Link.

Earlier: WACV18(1597-1606)
Dataset, Image Restoration. Used for restoration challenges at CVPR. image classification, image enhancement, image restoration, learning (artificial intelligence), object detection, Visualization

Liu, X.W.[Xin-Wei], Pedersen, M.[Marius], Hardeberg, J.Y.[Jon Yngve],
CID:IQ: A New Image Quality Database,
Springer DOI
Dataset, Image Quality.

Sun, W.[Wen], Zhou, F.[Fei], Liao, Q.[Qingmin],
MDID: A multiply distorted image database for image quality assessment,
PR(61), No. 1, 2017, pp. 153-168.
Elsevier DOI
Dataset, Image Quality. Image database

Virtanen, T., Nuutinen, M., Vaahteranoksa, M., Oittinen, P., Hakkinen, J.,
CID2013: A Database for Evaluating No-Reference Image Quality Assessment Algorithms,
IP(24), No. 1, January 2015, pp. 390-402.
Dataset, Image Quality. cameras

Lin, J.Y.[Joe Yuchieh], Song, R.[Rui], Wu, C.H.[Chi-Hao], Liu, T.J.[Tsung-Jung], Wang, H.[Haiqiang], Kuo, C.C.J.[C.C. Jay],
MCL-V: A streaming video quality assessment database,
JVCIR(30), No. 1, 2015, pp. 1-9.
Elsevier DOI
Dataset, Video Streaming. Video quality

SAVAM, Visual Salience Dataset,
Saliency dataset.
WWW Link. Dataset, Saliency.
41 scenes, eyetracker, high res, left and right stereo views. Paper reference:
See also Semiautomatic visual-attention modeling and its application to video compression.

Anaya, J.[Josue], Barbu, A.[Adrian],
RENOIR-A dataset for real low-light image noise reduction,
JVCIR(51), 2018, pp. 144-154.
Elsevier DOI
Dataset, Noise Reduction. Image denoising, Denoising dataset, Low light noise, Poisson-Gaussian noise model

The Chinese University of Hong Kong,
Computer Vision Laboratory WWW Link.
Research Group, Hong Kong. PETA: Pedestrian Attribute Recognition At Far Distance,
Dataset, Pedestrians. HTML Version.
19,000 images. Large-scale Fashion (DeepFashion) Dataset,
2016. HTML Version.
Dataset, Fashion. 800,000 fashion images. In-Shop Clothes Retrieval Database.

Lotus Hill Institute,
Imageparsing WWW Link.
Research Group, China. Dataset, Segmentation. Code, Viewing. The Imageparsing site is devoted to providing ground truth datasets and Matlab code for annotation and viewing.
See also LHI Object Datasets.
See also LHI Sports Activity Dataset.
See also LHI Segmentation Dataset.
See also LHI Surveillance Dataset.

Robotics. WWW Link.
Visual Geometry Group WWW Link.
Research Group, UK. Active vision, visual geometry, medical imaging, manufacturing systems, sonar, robotics. Oxford Image Examples,
Dataset. HTML Version.

Swiss Federal Institute of Technology in Zurich,
ETHComputer Vision Lab: WWW Link.
Research Group, Switzerland. Interpretation of 2D and 3D image data sets from conventional and non-conventional image sources. Photogrammetry group: WWW Link.
Aerial Image Dataset,
Dataset, Aerial Images. WWW Link.

University Jaume I,
Institute of New Imaging Technologies WWW Link.
Computer Vision Group WWW Link.
Research Group, Spain. Spectral Imaging. Spectral Imaging Data Base,
Dataset, Spectral Imaging. WWW Link.

University of Toronto,
RBCV-TRAnd Toronto WWW Link.
eyeTap Personal Imaging Lab: WWW Link.
Research Group, Canada. Open Vidia code.
See also OpenVidia. Large group. CIFAR-10 and CIFAR-100 Datasets,
Dataset, Tiny Images. HTML Version.
10 classes, 10000 images per class. Or 100 classes t00 images each.

Abel Stock,
Commercial image database WWW Link.
Dataset, Images.

California Institute of Technology,
Computational Vision Group WWW Link.
Research Group, US. Computational foundations of vision. A number of datasets are available online. CalTech 101 Objects Categories,
Dataset, Objects. HTML Version.
CalTech 256 Objects Categories,
Dataset, Objects. WWW Link.
30607 images, 256 categories. CalTech 100 Natural Scenes,
Dataset, Natural Scenes. WWW Link.
CalTech 10000 Web Faces,
Dataset, Faces. WWW Link.
CalTech Turntable Images,
Dataset, 3D Data. WWW Link.
144 calibrated viewpoints, 3 lighting variations. CalTech Archived Images,
Dataset, Images. HTML Version.
CalTech-UCSD Birds 200 2011,
CUB-200-2011 Dataset, Images. HTML Version.
Dataset, Birds. Extension of the CUB-200 dataset.

Massachusetts Institute of Technology, AI Lab,
Computer Science and Artificial Intelligence Lab CSAILAI group memo MIT AI Memoor MIT AIor MIT AIMAI Memos are shorter reports. MIT AI-TRor MIT AI TRAI Tech Reports are longer (often the thesis). Also Project MAC Technical Reports MAC-TRMost are available through: AI TR and Memo series go to 2004, then the CSAIL series. WWW Link.
CS & AI Lab Vision Research: WWW Link.
Activity, learning, medical vision, and vision interfaces. Perceptual Science Group: WWW Link.
Sensing Perception Autonomy and Robot Kinetics WWW Link.
Motion Magnification WWW Link.
Research Group, US. MIT Places Database for Scene Recognition,
Dataset, Recognition.
WWW Link. 205 scene categories, 2.5Million images. SUN 397 Database,

Ohio State University,
Signal Analysis and Machine Perception Laboratory (SAMPL) WWW Link.
Research Group, US. Broad research areas, hyper and multi-spectral, aerial images, medical images, range processing, human motion, inspection. Various datasets for 2-D and 3-D data. OSU Datasets,
Dataset, Images. HTML Version.

PrincetonComputer Science Department. Computer vision group. WWW Link.
Research Group, US. Human action classification. Dataset. WWW Link.
SUNRGBD: A RGB-D Scene Understanding Benchmark Suite,
Dataset, RGBD. WWW Link.
Indoor Scenes.

Stanford University, Computer Science Departent,
Technical report STAN-CSsome as Stanford AIThe Stanford Vision Lab: WWW Link.
Also: Stanford Vision and Imaging Science and Technology WWW Link.
Research Group, US. Also: Make3D moved to Cornell
See also Cornell University. Cars 196 Dataset,
Dataset, Vehicles. HTML Version.
196 classes of cars, 16,185 images.

University of Illinois,
Urbana-Champaign Various Departments, UIUCOr IllinoisVision Lab page: WWW Link.
Quantitative Light Imaging (QLI) Laboratory WWW Link.
Research Group, US. Robotics, Textures, 3-D recognition and representation, cameras, rendering, HCI. University of Illinois Datasets,
Dataset, Texture. 25 textures, 40 samples. Dataset, Natural Scenes. 15 Categories. Dataset, Stereo Data. 9 objects, 80 images Dataset, Multi-View Data. 10 datasets, 24 images of a single object each. Dataset, Visual Hull. Dataset, Object Recognition. Birds, Butterflys, etc. Dataset, Video. WWW Link.

University of Southern California, Signal and Image Processing,
Research Group, US. Dataset, Images. Image processing. Some of the old standard image datasets (texture, vehicles, compression).

Marszalek, M.[Marcin], Schmid, C.[Cordelia],
Accurate Object Recognition with Shape Masks,
IJCV(97), No. 2, April 2012, pp. 191-209.
WWW Link.

Accurate Object Localization with Shape Masks,
Dataset, People.
WWW Link. The dataset includes annotations. Derived from Graz dataset.
WWW Link.

Matching Challenge Dataset,
2020. Dataset, Matching.
WWW Link. Phototourism dataset. Large baseline matching.

Yang, G.[Gehua], Stewart, C.V.[Charles V.], Sofka, M.[Michal], Tsai, C.L.[Chia-Ling],
Registration of Challenging Image Pairs: Initialization, Estimation, and Decision,
PAMI(29), No. 11, November 2007, pp. 1973-1989.
Dataset, Matching.
HTML Version.
Automatic robust image registration system: Initialization, estimation, and decision,

Zhang, J.[Juncheng], Liao, Q.[Qingmin], Liu, S.[Shaojun], Ma, H.[Haoyu], Yang, W.[Wenming], Xue, J.H.[Jing-Hao],
Real-MFF: A large realistic multi-focus image dataset with ground truth,
PRL(138), 2020, pp. 370-377.
Elsevier DOI
Dataset, Multi-Focus. Image fusion, Multi-focus images, Multi-focus dataset, Deep learning

Goyette, N., Jodoin, P.M., Porikli, F.M., Konrad, J., Ishwar, P.,
A Novel Video Dataset for Change Detection Benchmarking,
IP(23), No. 11, November 2014, pp. 4663-4679.
Dataset, Change Detection. Adaptive optics

Wang, Y.[Yi], Jodoin, P.M.[Pierre-Marc], Porikli, F.M.[Fatih M.], Konrad, J.[Janusz], Benezeth, Y.[Yannick], Ishwar, P.[Prakash],
CDnet 2014: An Expanded Change Detection Benchmark Dataset,
Dataset, Change Detection.

Goyette, N.[Nil], Jodoin, P.M.[Pierre-Marc], Porikli, F.M.[Fatih M.], Konrad, J.[Janusz], Ishwar, P.[Prakash], A new change detection benchmark dataset,
Dataset, Change Detection.

Walas, K.[Krzysztof], Leonardis, A.[Aleš],
UoB highly occluded object challenge (UoB-HOOC),
WWW Link. Dataset, Object Detection.

Wang, Y.M.[Ya-Ming], Tan, X.[Xiao], Yang, Y.[Yi], Li, Z., Liu, X., Zhou, F., Davis, L.S.,
A Refined 3D Pose Dataset for Fine-Grained Object Categories,
Dataset, Object Recognition.
HTML Version. image segmentation, object recognition, pose estimation, statistical analysis, image segmentation networks, IoU, Fine grained objects

A large-scale video dataset for 6D object pose estimation. provides accurate 6D poses of 21 objects from the YCB dataset observed in 92 videos with 133,827 frames.
WWW Link. Dataset, Pose Estimation.

Drost, B.[Bertram], Ulrich, M.[Markus], Bergmann, P., Härtinger, P., Steger, C.T.[Carsten T.],
Introducing MVTec ITODD: A Dataset for 3D Object Recognition in Industry,
Dataset, Object Recognition. Cameras, Engines, Gray-scale, Object detection, Sensor phenomena and characterization.

Hodan, T.[Tomáš], Michel, F.[Frank], Brachmann, E.[Eric], Kehl, W.[Wadim], Buch, A.G.[Anders Glent], Kraft, D.[Dirk], Drost, B.[Bertram], Vidal, J.[Joel], Ihrke, S.[Stephan], Zabulis, X.[Xenophon], Sahin, C.[Caner], Manhardt, F.[Fabian], Tombari, F.[Federico], Kim, T.K.[Tae-Kyun], Matas, J.G.[Jirí G.],
BOP: Benchmark for 6D Object Pose Estimation,
ECCV18(X: 19-35).
Springer DOI
Dataset, Object Pose.

Peters, G.[Gabriele], Zitova, B.[Barbara], von der Malsburg, C.[Christoph],
How to measure the pose robustness of object views,
IVC(20), No. 5-6, 15 April 2002, pp. 341-348.
Elsevier DOI
BMVC issue
And: IVC(20), No. 4, April 2002, pp. 249-256.
Elsevier DOI
HTML Version.
Dataset, 3-D Data.

Stegmann, M.B.[Mikkel B.],
Active Appearance Models,
WWW Link. Code, Active Appearance Model. Dataset, Active Appearance Model. AAM code and information.
See also Technical University of Denmark.

Luo, C.[Cai], Yu, L.J.[Lei-Jian], Yang, E.[Erfu], Zhou, H.Y.[Hui-Yu], Ren, P.[Peng],
A benchmark image dataset for industrial tools,
PRL(125), 2019, pp. 341-348.
Elsevier DOI
Dataset, Tools. Benchmark, Industrial tools, Image dataset

MIT 67 Indoor Dataset,
Dataset, Indoor Images.
HTML Version.
See also Recognizing indoor scenes.

Yang, K., Russakovsky, O., Deng, J.,
SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition,
Dataset, Spatial Relations.
WWW Link. crowdsourcing, image capture, image recognition, image sampling, object recognition, SpatialSense benchmark, Genomics

Section, Multiple Entries: 13.4.6 Object Recognition, Retrieval Datasets Chapter Contents (Back)
Evaluation, Recognition. Dataset, Objects. Dataset, Retrieval.
See also Visual Question Answering, Query, VQA, Visual Dialog.

The PASCAL Object Recognition Database Collection,
2006. Dataset, Objects.
HTML Version. Various datasets for object recognition. Pointers to some of the others.

Video Objects: A Test Database for Video Object Recognition,
2006. Dataset, Objects.
HTML Version. 180 videos of 15 objects.

Animals with Attributes: A dataset for Attribute Based Classification,
2006. Dataset, Objects.
WWW Link. 30,000+ images, 40 animal classes.

Image Net,
WWW Link. Dataset, Objects. Large set of images (or sets of datasets) for recognition. Related to ImageNet Challanges for recognition. 14Million+ images. Links to Stanford
See also Stanford University, Computer Science Departent. and Princeton.
See also Princeton.

Washington Ground Truth Image Database,
CBIR dataset. Online2004
WWW Link. Dataset. Dataset, Retrieval.

LHI Object Datasets,
Includes hand segmentations, and annotations. Online2004
HTML Version. Dataset. Dataset, Object Recognition. Transportation images, Animals, Aerial Images, Objects, Dataset also includes other data.
See also Lotus Hill Institute.

NEC Animal Dataset,
WWW Link. Dataset. Dataset, Object Recognition. It consists of about 5000 high quality images from 60 toy animals taken at different poses against a plain background.

WWW Link. Dataset, Object Recognition. Photo search for professional use. Searches stock databases, you then purchase the image for use. Part of CogniSign LLC.

15 Scene Dataset,
Dataset, Objects.
HTML Version. The 15 scene categories are office, kitchen, living room, bedroom, store, industrial, tall building, inside cite, street, highway, coast, open country, mountain, forest, and suburb. Images in the dataset are about 250*300 resolution, with 210 to 410 images per class.

Video Dataset Overview,
WWW Link. Dataset, Overview. A good collection of Video datasets for various uses, activity, instruction, sports, etc..

Geusebroek, J.M.[Jan-Mark], Burghouts, G.J.[Gertjan J.], Smeulders, A.W.M.[Arnold W.M.],
The Amsterdam Library of Object Images,
IJCV(61), No. 1, January 2005, pp. 103-112.
DOI Link

WWW Link. Dataset, Objects. 1000 objects over 100 images per object.

Torralba, A.B.[Antonio B.], Fergus, R.[Rob], Freeman, W.T.[William T.],
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition,
PAMI(30), No. 11, November 2008, pp. 1958-1970.
WWW Link.

And: CSAIL-TR-2007-024, 2007. Dataset, Retrieval. Images from the WWW, associated with a noun. Large comprehensive dataset. Dataset with segmentations.

Russell, B.[Bryan], Torralba, A.B.[Antonio B.], Freeman, W.T.[William T.],
LableMe: The Open Annotation Tool,
WWW Link.
Dataset, Retrieval. Code, Annotation. The site for the annotation tool, also the video version.

Zhou, B.[Bolei], Lapedriza, A.[Agata], Khosla, A.[Aditya], Oliva, A.[Aude], Torralba, A.B.[Antonio B.],
Places: A 10 Million Image Database for Scene Recognition,
PAMI(40), No. 6, June 2018, pp. 1452-1464.
Dataset, Retrieval. Context, Databases, Image recognition, Semantics, Sun, Training, Visualization, Scene classification, deep feature, deep learning, visual recognition

Escalante, H.J.[Hugo Jair], Hernandez, C.A.[Carlos A.], Gonzalez, J.A.[Jesus A.], Lopez-Lopez, A., Montes-y-Gomez, M.[Manuel], Morales, E.F.[Eduardo F.], Sucar, L.E.[L. Enrique], Villasenor, L.[Luis], Grubinger, M.[Michael],
The segmented and annotated IAPR TC-12 benchmark,
CVIU(114), No. 4, April 2010, pp. 419-428.
Elsevier DOI
Dataset, Retrieval. Data set creation; Ground truth collection; Evaluation metrics; Automatic image annotation; Image retrieval

Russakovsky, O.[Olga], Deng, J.[Jia], Su, H.[Hao], Krause, J.[Jonathan], Satheesh, S.[Sanjeev], Ma, S.[Sean], Huang, Z.H.[Zhi-Heng], Karpathy, A.[Andrej], Khosla, A.[Aditya], Bernstein, M.[Michael], Berg, A.C.[Alexander C.], Fei-Fei, L.[Li],
ImageNet Large Scale Visual Recognition Challenge,
IJCV(115), No. 3, December 2015, pp. 211-252.
Springer DOI
Dataset, Object Category. Object category classification and detection on hundreds of object categories and millions of images.

Loh, Y.P.[Yuen Peng], Chan, C.S.[Chee Seng],
Getting to know low-light images with the Exclusively Dark dataset,
CVIU(178), 2019, pp. 30-42.
Elsevier DOI
Dataset, Low Light.

Aizawa, K., Fujimoto, A., Otsubo, A., Ogawa, T., Matsui, Y., Tsubota, K., Ikuta, H.,
Building a Manga Dataset 'Manga109' With Annotations for Multimedia Applications,
MultMedMag(27), No. 2, April 2020, pp. 8-18.
Dataset, Manga. Machine learning, Visualization, Character recognition, Art, Machine learning algorithms, Task analysis

Kuznetsova, A.[Alina], Rom, H.[Hassan], Alldrin, N.[Neil], Uijlings, J.[Jasper], Krasin, I.[Ivan], Pont-Tuset, J.[Jordi], Kamali, S.[Shahab], Popov, S.[Stefan], Malloci, M.[Matteo], Kolesnikov, A.[Alexander], Duerig, T.[Tom], Ferrari, V.[Vittorio],
The Open Images Dataset V4,
IJCV(128), No. 7, July 2020, pp. 1956-1981.
Springer DOI
Dataset, Object Detection. 9.2M images with unified annotations.
HTML Version.

Anderson, C.[Connor], Teuscher, A.[Adam], Anderson, E.[Elizabeth], Larsen, A.[Alysia], Shirley, J.[Josh], Farrell, R.[Ryan],
Have Fun Storming the Castle(s)!,
WWW Link.
Dataset, Castles. 2400 individual castles, palaces and fortresses from more than 90 countries, contains more than 770K images. Visualization, Image recognition, Geology, Computational modeling, Image retrieval

Figueiredo, A.[Augusto], Brayan, J.[Johnata], Reis, R.O.[Renan Oliveira], Prates, R.[Raphael], Schwartz, W.R.[William Robson],
MoRe: A Large-Scale Motorcycle Re-Identification Dataset,
WWW Link.
Dataset, Vehicles. Training, Deep learning, Computational modeling, Surveillance, Motorcycles, Traffic control

Le, H.A.[Hoang-An], Mensink, T.[Thomas], Das, P.[Partha], Karaoglu, S.[Sezer], Gevers, T.[Theo],
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes,
WWW Link.
Dataset, Outdoor Scenes. Deep learning, Image segmentation, Image color analysis, Computational modeling, Semantics

Scheck, T.[Tobias], Seidel, R.[Roman], Hirtz, G.[Gangolf],
Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning,
Dataset, Fisheye Images. Cameras, Image segmentation, Object detection, Semantics, Solid modeling, Rendering (computer graphics)

Behley, J., Garbade, M., Milioto, A., Quenzel, J., Behnke, S., Stachniss, C., Gall, J.,
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences,
Dataset, LiDAR. distance measurement, image segmentation, optical radar, stereo image processing, LiDAR sequences, Lasers

Wang, X., Wu, J., Chen, J., Li, L., Wang, Y., Wang, W.Y.,
VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research,
WWW Link.
Dataset, . language translation, linguistics, natural language processing, video signal processing, unified multilingual model, Social network services

Gu, S., Lugmayr, A., Danelljan, M., Fritsche, M., Lamour, J., Timofte, R.,
DIV8K: DIVerse 8K Resolution Image Dataset,
Dataset, High Resolution. convolutional neural nets, image resolution, learning (artificial intelligence), CNN, image processing

Mauceri, C.[Cecilia], Palmer, M.[Martha], Heckman, C.[Christoffer],
SUN-Spot: An RGB-D Dataset With Spatial Referring Expressions,
Dataset, Recognition. image colour analysis, object detection, SLAM (robots), spatial referring expressions, SUN-Spot, objects localization, multimodal

Sølund, T.[Thomas], Buch, A.G.[Anders Glent], Krüger, N.[Norbert], Aanæs, H.[Henrik],
A Large-Scale 3D Object Recognition Dataset,
Dataset, Object Recognition.
WWW Link. object recognition

Hua, B.S.[Binh-Son], Pham, Q.H.[Quang-Hieu], Nguyen, D.T.[Duc Thanh], Tran, M.K.[Minh-Khoi], Yu, L.F.[Lap-Fai], Yeung, S.K.[Sai-Kit],
SceneNN: A Scene Meshes Dataset with aNNotations,
Dataset, RGB-D.
WWW Link. Cameras

Rotman, D.[Daniel], Gilboa, G.[Guy],
A Depth Restoration Occlusionless Temporal Dataset,
Dataset, RGB-D.

Zhang, J.J.[Jun-Jie], Zhang, J.[Jian], Lu, J.F.[Jian-Feng], Shen, C.H.[Chun-Hua], Curr, K.[Kate], Phua, R.[Robin], Neville, R.[Richard], Edmonds, E.[Elise],
SLNSW-UTS: A Historical Image Dataset for Image Multi-Labeling and Retrieval,
Dataset, Object Recognition. 29713 images, 119 labels.

Xiang, Y.[Yu], Kim, W.[Wonhui], Chen, W.[Wei], Ji, J.W.[Jing-Wei], Choy, C.[Christopher], Su, H.[Hao], Mottaghi, R.[Roozbeh], Guibas, L.J.[Leonidas J.], Savarese, S.[Silvio],
ObjectNet3D: A Large Scale Database for 3D Object Recognition,
ECCV16(VIII: 160-176).
Springer DOI
Dataset, Object Recognition.
WWW Link.

Lin, T.Y.[Tsung-Yi], Maire, M.[Michael], Belongie, S.J.[Serge J.], Hays, J.[James], Perona, P.[Pietro], Ramanan, D.[Deva], Dollár, P.[Piotr], Zitnick, C.L.[C. Lawrence],
Microsoft COCO: Common Objects in Context,
ECCV14(V: 740-755).
Springer DOI
Dataset, Objects.
WWW Link.

Flickr30k Dataset,
From image descriptions to visual denotations. WWW Link.
Dataset, Visual Question Answering. Extension of Flickr 8k dataset.

Plummer, B.A.[Bryan A.], Wang, L.[Liwei], Cervantes, C.M.[Chris M.], Caicedo, J.C.[Juan C.], Hockenmaier, J.[Julia], Lazebnik, S.[Svetlana],
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models,
IJCV(123), No. 1, May 2017, pp. 74-93.
Springer DOI

Earlier: ICCV15(2641-2649)
Dataset, Object Recognition. Benchmark testing

Fanello, S.R.[Sean Ryan], Ciliberto, C.[Carlo], Santoro, M.[Matteo], Natale, L.[Lorenzo], Metta, G.[Giorgio], Rosasco, L.[Lorenzo], Odone, F.[Francesca],
iCub World: Friendly Robots Help Building Good Vision Data-Sets,
Dataset, Object Recognition. Human Robot Interaction; Object Categorization Dataset; iCub

Ponomarenko, N.[Nikolay], Ieremeiev, O.[Oleg], Lukin, V.[Vladimir], Jin, L.[Lina], Egiazarian, K.O.[Karen O.],
A New Color Image Database TID2013: Innovations and Results,
Springer DOI
Dataset, Color Images.

Ponce, J., Berg, T.L., Everingham, M.R., Forsyth, D.A., Hebert, M., Lazebnik, S.[Svetlana], Marszalek, M., Schmid, C., Russell, B.C., Torralba, A., Williams, C.K.I., Zhang, J., Zisserman, A.,
Dataset Issues in Object Recognition,
Springer DOI
Dataset, Discussion.

Campbell, R., and Flynn, P.J.,
A WWW-Accessible 3D Image and Model Database for Computer Vision Research,
And: EEMTV98(xx) Dataset, 3-D Data.
HTML Version.

Nene, S.A., Nayar, S.K.[Shree K.], Murase, H.[Hiroshi],
Columbia Object Image Library (COIL-100),
ColumbiaTechnical Report CUCS-006-96, February 1996.
PS File. Also:
WWW Link. Also the COIL-20 database.
WWW Link. Dataset, Objects.

Bileschi, S.M.[Stanley M.],
CBCL StreetScenes Challenge Framework,
WWW Link. Dataset, Object Detection. Primarily for Cars, people, and street scenes. Data is labeled.

Hoiem, D.[Derek], Efros, A.A.[Alexei A.], Hebert, M.[Martial],
Recovering Surface Layout from an Image,
IJCV(75), No. 1, October 2007, pp. 151-172.
Springer DOI

Geometric Context from a Single Image,
ICCV05(I: 654-661).
Dataset, Recognition. The example data is available:
HTML Version. Kanade issue. Coarse properties (ground plane, sky, planar regions) from one image. Probabilistic approach to estimate 3D geometry so that not every possible view is needed.

Medical Dataset Archive,
2006. Dataset, Medical Images.
WWW Link. Variety of medical data. CT dataset available from related web site.

Visible Human Project,
1994. Dataset, Medical Images.
HTML Version. Complete data in MRI, CT, slices.

MOTA Object Tracking Benchmark,
2021 for workshop.
WWW Link. Dataset, Cell Tracking.

CR Chisto Labeled Nuclei Dataset,
WWW Link. Dataset, Nuclei.
Dataset of colorectal cancer histology images consisting of nearly 30,000 dotted nuclei with over 22,000 labeled with the type of cell they belong to.

FIRE Fundus Image Registration Dataset,
WWW Link. Dataset, Retinal. Dataset, Registration.
134 retinal image pairs and ground truth for registration.

Kauppi, T., Kalesnykiene, V., Kamarainen, J.K., Lensu, L., Sorri, I., Raninen, A., Voutilainen, R., Uusitalo, H., Kalviainen, H., Pietila, J.,
The DIARETDB1 diabetic retinopathy database and evaluation protocol,
PDF File.
Dataset, Retina.

MiniMammographic Database,
WWW Link. Dataset, Mammography.

DDSM: Digital Database for Screening Mammography,
2000, USF.
HTML Version. Dataset, Mammography.

Developing Human Connectome Project (dHCP),
WWW Link. Dataset, fMRI. The imaging data includes structural imaging, structural connectivity data (diffusion MRI) and functional connectivity data (resting-state fMRI).

Andreopoulos, A.[Alexander], Tsotsos, J.K.[John K.],
Cardiac MRI dataset,
WWW Link. Dataset, Cardiac MRI.

CoronARe: A Coronary Artery Reconstruction Challenge,
2017. Dataset, Angiography.
WWW Link. 3D Reconstrucion challange dataset.

Huang, Y.[Yan], Essa, I.A.[Irfan A.],
Tracking Multiple Objects through Occlusions,
CVPR05(II: 1051-1058).
WWW Link. Dataset, Actions.

And: CVPR05(II: 1182).
See also Georgia Tech.

Zimmermann, K.[Karel], Matas, J.G.[Jirí G.], Svoboda, T.[Thomáš],
Tracking by an Optimal Sequence of Linear Predictors,
PAMI(31), No. 4, April 2009, pp. 677-692.
Code, Tracking. Dataset, Tracking.
Earlier: A1, A3, A2:
Simultaneous learning of motion and appearance,

Earlier: A1, A3, A2:
Adaptive Parameter Optimization for Real-time Tracking,

Earlier: A1, A3, A2:
Multiview 3D Tracking with an Incrementally Constructed 3D Model,
Learning approach to tracking. Estimation of the pose given the pose of the previous frame. Matlab implementation available.
WWW Link.

Hopkins 155,
Motion Dataset Online2007.
WWW Link. Dataset, Motion. Testing feature based motion segmentation algorithms.
See also Johns Hopkins University.

Tracking Any Object, TAO, Dataset,
Motion Dataset Online
WWW Link. Dataset, Tracking. 2,907 high resolution videos, captured in diverse environments.

Visual Object Tracking Challenges, VOT,
Tracking Challenges and datasets. Online
HTML Version. Dataset, Tracking. Various VOT workshop datasets.
See also Visual Object Tracking Challenge.

OTCBVS Benchmark Dataset Collection,
WWW Link. Dataset, Tracking. Dataset, Face Recognition. Collection of datasets for benchmarking realted to the related conferences. Includes face dataset.

UCF Parking Lot Tracking,
WWW Link. Dataset, Tracking. Tracking multiple people in parking lot.
See also Part-based multiple-person tracking with partial occlusion handling.
See also GMCP-Tracker: Global Multi-object Tracking Using Generalized Minimum Clique Graphs.

Dubuisson, S.[Séverine], Gonzales, C.[Christophe],
A survey of datasets for visual tracking,
MVA(27), No. 1, January 2016, pp. 23-52.
WWW Link.
Survey, Tracking. Dataset, Tracking.

Li, A., Lin, M., Wu, Y., Yang, M., Yan, S.,
NUS-PRO: A New Visual Tracking Challenge,
PAMI(38), No. 2, February 2016, pp. 335-349.
Dataset, Tracking. Airplanes

Huang, L.H.[Liang-Hua], Zhao, X.[Xin], Huang, K.Q.[Kai-Qi],
GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild,
PAMI(43), No. 5, May 2021, pp. 1562-1577.
WWW Link. Dataset, Tracking. Training, Object tracking, Databases, Protocols, Benchmark testing, Servers, Object tracking, benchmark dataset, performance evaluation

Dendorfer, P.[Patrick], Osep, A.[Aljosa], Milan, A.[Anton], Schindler, K.[Konrad], Cremers, D.[Daniel], Reid, I.D.[Ian D.], Roth, S.[Stefan], Leal-Taixé, L.[Laura],
MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking,
IJCV(129), No. 4, April 2021, pp. 845-881.
Springer DOI
WWW Link. Dataset, Motion Tracking. There are a series of related datasets for annual challenges.

Bondi, E., Jain, R., Aggrawal, P., Anand, S., Hannaford, R., Kapoor, A., Piavis, J., Shah, S., Joppa, L., Dilkina, B., Tambe, M.,
BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos,
Dataset, Tracking. Videos, Cameras, Surveillance, Animals, Task analysis, Benchmark testing

Dave, A.[Achal], Khurana, T.[Tarasha], Tokmakov, P.[Pavel], Schmid, C.[Cordelia], Ramanan, D.[Deva],
TAO: A Large-scale Benchmark for Tracking Any Object,
Springer DOI
Dataset, Tracking.

Lukezic, A., Kart, U., Käpylä, J., Durmush, A., Kamarainen, J., Matas, J., Kristan, M.,
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark,
Dataset, Tracking. image colour analysis, image sequences, object detection, object tracking, pose estimation, most diverse dataset, Robot sensing systems

Müller, M.[Matthias], Bibi, A.[Adel], Giancola, S.[Silvio], Alsubaihi, S.[Salman], Ghanem, B.[Bernard],
TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild,
ECCV18(I: 310-327).
Springer DOI
Dataset, Tracking.

Valmadre, J.[Jack], Bertinetto, L.[Luca], Henriques, J.F.[João F.], Tao, R.[Ran], Vedaldi, A.[Andrea], Smeulders, A.W.M.[Arnold W. M.], Torr, P.H.S.[Philip H. S.], Gavves, E.[Efstratios],
Long-Term Tracking in the Wild: A Benchmark,
ECCV18(III: 692-707).
Springer DOI
Dataset, Tracking.

Zhang, S.[Shu], Staudt, E.[Elliot], Faltemier, T.[Tim], Roy-Chowdhury, A.K.[Amit K.],
A Camera Network Tracking (CamNeT) Dataset and Performance Baseline,
Dataset, Camera Tracking.
WWW Link. Cameras; Legged locomotion; Lighting; Target tracking; Trajectory; Videos

Jaynes, C., Kale, A., Sanders, N., Grossmann, E.,
The Terrascope Dataset: Scripted Multi-Camera Indoor Video Surveillance with Ground-truth,
WWW Link.
Dataset, Surveillance.

PETS Benchmark Datasets,
Online2006 Dataset:
HTML Version. Dataset, Surveillance. 2014 Dataset:
HTML Version. 2015 Dataset:
HTML Version. 2016 Dataset:
HTML Version.

MIT Pedestrian Database MITP,
HTML Version. Dataset, Surveillance.

UCF Action Recogniton Dataset 101,
WWW Link.

Earlier: UCF Action Recogniton Dataset 50,
WWW Link. Dataset, Surveillance.
101 action categories, consisting of realistic videos taken from youtube. UCF 101 is an extension of UCF 50. Categories include: Baseball Pitch, Basketball Shooting, Bench Press, Biking, Biking, Billiards Shot,Breaststroke, Clean and Jerk, Diving, Drumming, Fencing, Golf Swing, Playing Guitar, High Jump, Horse Race, Horse Riding, Hula Hoop, Javelin Throw, Juggling Balls, Jump Rope, Jumping Jack, Kayaking, Lunges, Military Parade, Mixing Batter, Nun chucks, Playing Piano, Pizza Tossing, Pole Vault, Pommel Horse, Pull Ups, Punch, Push Ups, Rock Climbing Indoor, Rope Climbing, Rowing, Salsa Spins, Skate Boarding, Skiing, Skijet, Soccer, Juggling, Swing, Playing Tabla, TaiChi, Tennis Swing, Trampoline Jumping, Playing Violin, Volleyball Spiking, Walking with a dog, and Yo Yo. The printed reference:
See also UCF101: A Dataset of 101 Human Action Classes from Videos in The Wild.

WWW Link. Dataset, Surveillance.
Aerobic actions using the Inertial Measurement Unit (IMU) on an Apple iPhone. Biking, Climbing Stairs, Descending Stairs, Gym Biking, Jump Roping, Running, Standing, Treadmill Walking and Walking.
See also Macro-Class Selection for Hierarchical K-NN Classification of Inertial Sensor Data. for the paper.

The KITTI Vision Benchmark Suite,
WWW Link. Dataset, Road Scenes. Stereo, Lidar, GPS, etc.
See also Vision meets robotics: The KITTI dataset.

Hollywood2 Human Actions and Scenes Dataset,
WWW Link. Dataset, Surveillance.
Part originally from:
See also Actions in context.

HMDB: a large human motion database,
WWW Link. Dataset, Surveillance.
51 actions.
See also HMDB: A large video database for human motion recognition.

TRECVID Workshop DAta,
HTML Version. Dataset, Surveillance.
Surveillance datasets from 2001 to 2017.

Privacy-Preserving Visual Recognition PA-HMDB51,
WWW Link. Dataset, Actions. Dataset, Privacy. The dataset contains 592 videos selected from the HMDB51 dataset (
See also HMDB: A large video database for human motion recognition. ). For each video, we provide with frame-level annotation of five privacy attributes: skin color, gender, face, nudity, and relationship.
See also Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study.

HVU Dataset,
WWW Link. Dataset, Action. For Holistic Video Understanding workshop

WWW Link. Dataset, Action. Dataset, Daily Activities. First-person (egocentric) vision; multi-faceted non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities in the kitchen over multiple days.

Kay, W.[Will], Carreira, J.[Joao], Simonyan, K.[Karen], Zhang, B.[Brian], Hillier, C.[Chloe], Vijayanarasimhan, S.[Sudheendra], Viola, F.[Fabio], Green, T.[Tim], Back, T.[Trevor], Natsev, P.[Paul], Suleyman, M.[Mustafa], Zisserman, A.[Andrew],
The Kinetics Human Action Video Dataset,
WWW Link.
WWW Link. Dataset, Actions. Dataset, Human Action.

Tenorth, M.[Moritz], Bandouch, J.[Jan], Beetz, M.[Michael],
The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition,
Dataset, Activity Recognition.

Guerra-Filho, G.[Gutemberg], Biswas, A.[Arnab],
The human motion database: A cognitive and parametric sampling of human motion,
IVC(30), No. 3, March 2012, pp. 251-261.
Elsevier DOI

Earlier: FG11(103-110).
Dataset, Activity Recognition. Human motion database; Quantitative evaluation; Parametric and cognitive sampling; Motion synthesis and analysis

Chaquet, J.M.[Jose M.], Carmona, E.J.[Enrique J.], Fernandez-Caballero, A.[Antonio],
A survey of video datasets for human action and activity recognition,
CVIU(117), No. 6, June 2013, pp. 633-659.
Elsevier DOI
Survey, Activity Recognition. Dataset, Activity Recognition. Human action recognition; Human activity recognition; Database; Dataset; Review; Survey

Chavarriaga, R.[Ricardo], Sagha, H.[Hesam], Calatroni, A.[Alberto], Digumarti, S.T.[Sundara Tejaswi], Tröster, G.[Gerhard], del R. Millán, J.[José], Roggen, D.[Daniel],
The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition,
PRL(34), No. 15, 2013, pp. 2033-2042.
Elsevier DOI
Dataset, Activity Recognition. Activity recognition

Barrett, D.P.[Daniel Paul], Xu, R.[Ran], Yu, H.N.[Hao-Nan], Siskind, J.M.[Jeffrey Mark],
Collecting and annotating the large continuous action dataset,
MVA(27), No. 7, October 2016, pp. 983-995.
Springer DOI
Dataset, Actions. LCA Dataset.

Hadfield, S.[Simon], Lebeda, K.[Karel], Bowden, R.[Richard],
Hollywood 3D: What are the Best 3D Features for Action Recognition?,
IJCV(121), No. 1, January 2017, pp. 95-110.
Springer DOI

Earlier: A1, A3, Only:
Hollywood 3D: Recognizing Actions in 3D Natural Scenes,
Dataset, Attion Recognition. Hollywood3D dataset. 3.5d

Monfort, M.[Mathew], Andonian, A.[Alex], Zhou, B.L.[Bo-Lei], Ramakrishnan, K.[Kandan], Bargal, S.A.[Sarah Adel], Yan, T.[Tom], Brown, L.[Lisa], Fan, Q.F.[Quan-Fu], Gutfreund, D.[Dan], Vondrick, C.[Carl], Oliva, A.[Aude],
Moments in Time Dataset: One Million Videos for Event Understanding,
PAMI(42), No. 2, February 2020, pp. 502-508.
WWW Link. Dataset, Action. Videos, Visualization, Feature extraction, Vocabulary, Animals, Convolution, Video dataset, event recognition

Patino, L.[Luis], Ferryman, J.M.[James M.],
PETS 2014: Dataset and challenge,
Dataset, Surveillance. Cameras

Per, J.[Janez], Kenk, V.S.[Vildana Sulic], Mandeljc, R.[Rok], Kristan, M.[Matej], Kovacic, S.[Stanislav],
Dana36: A Multi-camera Image Dataset for Object Identification in Surveillance Scenarios,

Liu, C.[Ce], Freeman, W.T.[William T.], Adelson, E.H.[Edward H.], Weiss, Y.[Yair],
Human-assisted motion annotation,
Dataset, Motion.
WWW Link. Motion annotation then applied to datasets to provide ground truth.

LHI Surveillance Dataset,
Annotated surveillance images. Online2008
HTML Version. Dataset, Segmentation. Subset of larger dataset.
See also Lotus Hill Institute.

CLEAR: Classification of Events, Activities and Relationships,
WWW Link. Dataset, Activity Recogniton.

i-LIDS: Bag and vehicle detection challenge,
Online2007 AVSBS07
HTML Version. Dataset, Activity Recogniton. Data used at Advanced Video and Signal Based Surveillance, 2007.

Multimedia Event Detection,
Series of Event and Activity Detection evaluations.
WWW Link.
WWW Link.
WWW Link. Dataset, Activity Recogniton. MED13, MED12, MED11.

Multiview Extended Video with Activities,
MEVA Test 3:
WWW Link. Information also:
WWW Link. Dataset, Activity Recogniton. Dataset, MEVA. 333 hours of ground-camera and UAV videos and 28 hours of MEVA training Annotations dataset.
See also MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection.

PETS 2006 Benchmark Data,
Online2006 PETS06
HTML Version. Dataset, Activity Recogniton. Data used at International Workshop on Performance Evaluation of Tracking and Surveillance 2006.

PETS 2001 Benchmark Data,
Online2001 PETS01
WWW Link. Dataset, Activity Recogniton. Data used at International Workshop on Performance Evaluation of Tracking and Surveillance 2001.

OTCBVS Benchmark Dataset Collection,
WWW Link. Dataset, Activity Recogniton. Beyound the Visual Spectrum (IR especially). Data for various OTCBVS workshops.

YouTube-8M Dataset,
Labed video dataset.
WWW Link. Dataset, Video Database. 4700+ visual entities.

Fisher, R.B.[Robert B.],
CAVIAR Test Case Scenarios,
Online BookOctober 2004.
WWW Link. Dataset, Video. From the EC funded CAVIAR project (Context Aware Vision using Image-based Active Recognition). The sequences are labelled (in XML) with both the tracked persons and a semantic description of their activities. 81 video sequences comprising about 90K frames. These sequences include indoor plaza and shopping center observations of individuals and small groups of people walking, browsing, window shopping, fighting, meeting, leaving packages behind, collapsing, entering and exiting shops, etc.

Optic Flow Data,
Edinburgh2007. Smoothed flow sequences for the Waverly train station scene.
WWW Link. Dataset, Video. Behavior, pedestrian analysis.

BEHAVE Interactions Test Case Scenarios,
Edinburgh2007. Two views of various scenarios of people acting out various interactions.
WWW Link. Dataset, Video. Behavior, pedestrian analysis. Includes ground truth bounding boxes for much of the data.

Sigal, L.[Leonid], Balan, A.O.[Alexandru O.], Black, M.J.[Michael J.],
HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion,
IJCV(87), No. 1-2, March 2010, pp. xx-yy.
Springer DOI
Dataset, Human Motion.
Earlier: A1, A3, Only:
HumanEva: Synchronized Video and Motion Capture Dataset for Evaluation of Articulated Human Motion,
BrownTechnical Report CS-06-08, September 2006.
HTML Version. For the dataset:
HTML Version. Calibrated video sequences synchronized with motion capture data.

Li, L.Z.[Long-Zhen], Nawaz, T.[Tahir], Ferryman, J.M.,
PETS 2015: Datasets and challenge,
Dataset, PETS 2015. object detection

Oh, S.M.[Sang-Min], Hoogs, A.[Anthony], Perera, A.[Amitha], Cuntoor, N.[Naresh], Chen, C.C.[Chia-Chih], Lee, J.T.[Jong Taek], Mukherjee, S.[Saurajit], Aggarwal, J.K., Lee, H.T.[Hyung-Tae], Davis, L.S.[Larry S.], Swears, E.[Eran], Wang, X.Y.[Xiao-Yang], Ji, Q.A.[Qi-Ang], Reddy, K.K.[Kishore K.], Shah, M.[Mubarak], Vondrick, C.[Carl], Pirsiavash, H.[Hamed], Ramanan, D.[Deva], Yuen, J.[Jenny], Torralba, A.B.[Antonio B.], Song, B.[Bi], Fong, A.[Anesco], Roy-Chowdhury, A.[Amit], Desai, M.[Mita],
A large-scale benchmark dataset for event recognition in surveillance video,

And: AVSBS11(527-528).
Dataset, Action Recognition. Dataset, Event Recognition.

Harvey, A.[Adam], LaPlace, J.[Jules],,
WWW Link.
Dataset, Duke MTMC Dataset. Privacy issues in re-identification research and the use of large datasets.

MIT Car Database MITC,
HTML Version. Dataset, Vehicles.

PKU-VD Dataset,
2017 HTML Version.
Dataset, Vehicles. VD1: 1,097,649 images. 1,232 vehicle models and 11 colors. VD2: 807,260 images. 1,112 vehicle models and 11 colors. Reference:
See also Exploiting Multi-grain Ranking Constraints for Precisely Searching Visually-similar Vehicles.

PKU VehicleID Dataset,
2016 HTML Version.
Dataset, Vehicles. 10319 vehicles, 90196 images. Reference:
See also Deep Relative Distance Learning: Tell the Difference between Similar Vehicles.

Struwe, M.[Marvin], Hasler, S.[Stephan], Bauer-Wersing, U.[Ute],
Rendered Benchmark Data Set for Evaluation of Occlusion-Handling Strategies of a Parts-Based Car Detector,
Springer DOI
Dataset, Vehicle Detection.

Racing Bicycle Detection/Tracking from UAV Footage, UAV Detection,
Motion Datasets Online2019.
HTML Version. Dataset, Vehicle Tracking. Dataset, Drone Detection. Multiple datasets. UAV detection against variety of backgrounds.

Behrendt, K.,
Boxy Vehicle Detection in Large Images,
Dataset, Vehicles.
WWW Link. cameras, image resolution, image segmentation, object detection, road vehicles, traffic engineering computing, individual teams, dataset

UA-DETRAC Benchmark Suite,
WWW Link. Dataset, Traffic.

See also UA-DETRAC 2017: Report of AVSS2017 IWT4S Challenge on Advanced Traffic Monitoring.

Neuhold, G.[Gerhard], Ollmann, T.[Tobias], Bulò, S.R.[Samuel Rota], Kontschieder, P.[Peter],
The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes,
Dataset, Traffic. 25,000 images, 66 categories. computational geometry, data visualisation, image annotation, image resolution, image segmentation, road traffic, Visualization

Koschorrek, P.[Philipp], Piccini, T.[Tommaso], Oberg, P.[Per], Felsberg, M.[Michael], Nielsen, L.[Lars], Mester, R.[Rudolf],
A Multi-sensor Traffic Scene Dataset with Omnidirectional Video,
Dataset, Traffic. automotive

Da Cruz, S.D.[Steve Dias], Wasenmüller, O.[Oliver], Beise, H.P.[Hans-Peter], Stifter, T.[Thomas], Stricker, D.[Didier],
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark,
Dataset, Vehicle Surveilance.
WWW Link. Task analysis, Benchmark testing, Training, Automobiles, Cameras, Lightning

Massoz, Q., Langohr, T., Francois, C., Verly, J.G.,
The ULg multimodality drowsiness database (called DROZY) and examples of use,
Dataset, Driver Monitoring. Cameras

Xu, Z.B.[Zhen-Bo], Yang, W.[Wei], Meng, A.[Ajin], Lu, N.[Nanxue], Huang, H.[Huan], Ying, C.C.[Chang-Chun], Huang, L.S.[Liu-Sheng],
Towards End-to-End License Plate Detection and Recognition: A Large Dataset and Baseline,
ECCV18(XIII: 261-277).
Springer DOI
Dataset, License Plates.

Eraqi, H.M.[Hesham M.], Abouelnaga, Y.[Yehya], Saad, M.H.[Mohamed H.], Moustafa, M.N.[Mohamed N.],
Distracted Driver Dataset,
WWW Link.
Dataset, Driver Monitoring. Includes Distracted Driver V1 and Distracted Driver V2.

Zelnik-Manor, L.[Lihi], Irani, M.[Michal],
Statistical Analysis of Dynamic Actions,
PAMI(28), No. 9, September 2006, pp. 1530-1535.

Degeneracies, dependencies and their implications in multi-body and multi-sequence factorizations,
Weinland, D.[Daniel], Ronfard, R.[Remi], Boyer, E.[Edmond],
Free viewpoint action recognition using motion history volumes,
CVIU(103), No. 2-3, November-December 2006, pp. 249-257.
Elsevier DOI
Dataset, Action Recognition.
WWW Link.
Automatic Discovery of Action Taxonomies from Multiple Views,
CVPR06(II: 1639-1645).

And: A1, A3, A2:
Action Recognition from Arbitrary Views using 3D Exemplars,
Action recognition; View invariance; Volumetric reconstruction

Yu, L., Yang, Y., Huang, Z., Wang, P., Song, J., Shen, H.T.,
Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents,
IP(25), No. 12, December 2016, pp. 5689-5701.
Dataset, Video Events. UQE50 Dataset. UQ Event database with 50 pre-defined video events. Internet

Bossard, L.[Lukas], Guillaumin, M.[Matthieu], Van Gool, L.J.[Luc J.],
Event Recognition in Photo Collections with a Stopwatch HMM,
Dataset, Event Recognition. 61,000 images in 807 collections, with 14 social event classes.

Shi, Y.F.[Yi-Fan], Huang, Y.[Yan], Minnen, D., Bobick, A.F., Essa, I.A.,
Propagation networks for recognition of partially ordered sequential action,
CVPR04(II: 862-869).
HTML Version. Dataset, Actions.
See also Georgia Tech.

VIPeR: Viewpoint Invariant Pedestrian Recognition,
Pedestrian dataset. 2007. WWW Link.
Dataset, Pedestrians.

Wang, D.[Dan], Zhang, C.Y.[Chong-Yang], Cheng, H.[Hao], Shang, Y.F.[Yan-Feng], Mei, L.[Lin],
SPID: Surveillance Pedestrian Image Dataset and Performance Evaluation for Pedestrian Detection,
BEST16(III: 463-477).
Springer DOI
Dataset, Pedestrians.

Stanford 40 Actions,
A dataset for understanding human actions in still images HTML Version.
Dataset, Action Recognition.

People Playing Musical Instrument (PPMI),
A dataset of human and object interaction activities HTML Version.
Dataset, Action Recognition.

Kliper-Gross, O.[Orit], Hassner, T.[Tal], Wolf, L.B.[Lior B.],
The Action Similarity Labeling Challenge,
PAMI(34), No. 3, March 2012, pp. 615-621.
Dataset, Action Recognition. Labeled dataset. Same/not-same rather than recognition.

Distante, C.[Cosimo], Diraco, G.[Giovanni], Leone, A.[Alessandro],
Active Range Imaging Dataset for Indoor Surveillance,
BMVA(2010), No. 3, 2010, pp. 1-14.
PDF File.
Dataset, Action Recognition.

Blunsden, S.[Scott], Fisher, R.B.[Robert B.],
The BEHAVE video dataset: Ground truthed video for multi-person behavior classification,
BMVA(2010), No. 4, 2010, pp. 1-12.
PDF File.
Dataset, Action Recognition.

Hwang, S.[Soonmin], Park, J.[Jaesik], Kim, N.[Namil], Choi, Y.[Yukyung], Kweon, I.S.[In So],
Multispectral pedestrian detection: Benchmark dataset and baseline,
Dataset, Pedestrian Detection.

Wallraven, C.[Christian], Schultze, M.[Michael], Mohler, B.[Betty], Vatakis, A.[Argiro], Pastra, K.[Katerina],
The POETICON enacted scenario corpus: A tool for human and computational experiments on action understanding,
Dataset, Actions.

Munder, S., Gavrila, D.M.[Dariu M.],
An Experimental Study on Pedestrian Classification,
PAMI(28), No. 11, November 2006, pp. 1863-1868.
PDF File.
Dataset available:
HTML Version. Dataset, Pedestrians. DaimlerChrysler Res. Investigate global versus local and adaptive versus nonadaptive features. PCA coefficients, Haar wavelets, and local receptive fields (LRFs). SVM, Neural Nets, K-NN classifiers. Combination of SVMs with LRF features performs best. And boosted cascade of Haar wavelets is close.

Daimler Pedestrian Detection Benchmark,
HTML Version. Dataset, Pedestrian Detection. Dataset, Surveillance.
See also Daimler. Training set: 15,560 pedestrian and non-pedestrian samples. 6744 additional images. Test set: a sequence with more than 21,790 images with 56,492 pedestrian labels. From a vehicle in 27 minutes of urban driving. VGA resolution. Dataset used in:
See also Monocular Pedestrian Detection: Survey and Experiments.

Edinburgh Informatics Forum Pedestrian Database,
WWW Link. Dataset, Human Tracking. Dataset, Surveillance. Overhead views, of a building atrium. Several months of observations, with trajectories (computed).

Dalal, N.[Navneet],
INRIA Person Dataset,
WWW Link. Dataset, Human Motion. The collected dataset for the above paper, from various sources.

Wu, Y.[Yang], Liu, Y.L.[Yuan-Liu], Yuan, Z.J.[Ze-Jian], Zheng, N.N.[Nan-Ning],
IAIR-CarPed: A psychophysically annotated dataset with fine-grained and layered semantic labels for object recognition,
PRL(33), No. 2, 15 January 2012, pp. 218-226.
Elsevier DOI
Dataset, Pedestrian Detection. Object recognition; Image database; Object detection; Pedestrian detection; Psychophysical experiments

García-Martín, Á.[Álvaro], Martínez, J.M.[José M.], Bescós, J.[Jesús],
A corpus for benchmarking of people detection algorithms,
PRL(33), No. 2, 15 January 2012, pp. 152-156.
Elsevier DOI
Dataset, Person Detection. People detection; Ground-truth; Corpus; Dataset; Surveillance video

Sindagi, V., Yasarla, R., Patel, V.,
Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method,
Dataset, Crowd Counting. feature extraction, image classification, learning (artificial intelligence), object detection, Error analysis

Rasouli, A., Kotseruba, I., Kunic, T., Tsotsos, J.K.[John K.],
PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction,
Dataset, Pedestrians.
WWW Link. computer vision, intelligent transportation systems, pedestrians, large-scale dataset, pedestrian intention estimation, Vehicle dynamics

Zheng, L.[Liang], Bie, Z.[Zhi], Sun, Y.F.[Yi-Fan], Wang, J.D.[Jing-Dong], Su, C.[Chi], Wang, S.J.[Sheng-Jin], Tian, Q.[Qi],
MARS: A Video Benchmark for Large-Scale Person Re-Identification,
ECCV16(VI: 868-884).
Springer DOI
Dataset, Re-Identification.

Figueira, D.[Dario], Taiana, M.[Matteo], Nambiar, A.[Athira], Nascimento, J.C.[Jacinto C.], Bernardino, A.[Alexandre],
The HDA+ Data Set for Research on Fully Automated Re-identification Systems,
Springer DOI
Dataset, Re-Identification.

Ragheb, H.[Hossein], Velastin, S.A.[Sergio A.], Remagnino, P.[Paolo], Ellis, T.[Tim],
Human action recognition using robust power spectrum features,

ViHASi: Virtual human action silhouette data for the performance evaluation of silhouette-based action recognition methods,

And: VNBA08(77-84).
DOI Link

A Novel Approach for Fast Action Recognition using Simple Features,
Dataset, Action Recognition. Silhouette based action recognition.

Chakraborty, A.[Anirban], Das, A.[Abir], Roy-Chowdhury, A.K.[Amit K.],
Network Consistent Data Association,
PAMI(38), No. 9, September 2016, pp. 1859-1871.

Earlier: A2, A1, A3:
Consistent Re-identification in a Camera Network,
ECCV14(II: 330-345).
Springer DOI
Dataset, Re-Identification.
WWW Link.

Bialkowski, A., Denman, S., Sridharan, S., Fookes, C., Lucey, P.,
A Database for Person Re-Identification in Multi-Camera Surveillance Networks,
Dataset, Re-Identification.

Gou, M., Karanam, S., Liu, W., Camps, O., Radke, R.J.,
DukeMTMC4ReID: A Large-Scale Multi-camera Person Re-identification Dataset,
Dataset, Re-Identification. Airports, Benchmark testing, Cameras, Detectors, Feature extraction, Measurement, Surveillance

MoCA: Moving Camouflaged Animals dataset,
WWW Link. Dataset, Animals.
See also Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation.

Truong, C.[Charles], Barrois-Müller, R.[Rémi], Moreau, T.[Thomas], Provost, C.[Clément], Vienne-Jumeau, A.[Aliénor], Moreau, A.[Albane], Vidal, P.P.[Pierre-Paul], Vayatis, N.[Nicolas], Buffat, S.[Stéphane], Yelnik, A.[Alain], Ricard, D.[Damien], Oudre, L.[Laurent],
A Data Set for the Study of Human Locomotion with Inertial Measurements Units,
IPOL(9), 2019, pp. 381-390.
DOI Link
Dataset, Gait. Data set of 1020 multivariate gait signals collected with two inertial measurement units, from 230 subjects undergoing a fixed protocol: standing still, walking 10 m, turning around, walking back and stopping. In total, 8.5~h of gait time series are distributed.

Baseline Algorithm and Performance for Gait Based Human ID Challenge Problem,
2004, USF.
WWW Link. Dataset, Gait. Code, Gait.

Seely, R.D.[Richard D.], Samangooei, S.[Sina], Middleton, L.[Lee], Carter, J.N.[John N.], Nixon, M.S.[Mark S.],
The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset,
Dataset, Gait Recognition.

CMU Graphics Lab Motion Capture Database,
WWW Link. Dataset, Motion Capture. Code, Motion Capture. 2000+ examples of motion capture data. Includes some software.

Hofmann, M.[Martin], Geiger, J.[Jürgen], Bachmann, S.[Sebastian], Schuller, B.[Björn], Rigoll, G.[Gerhard],
The TUM Gait from Audio, Image and Depth (GAID) database: Multimodal recognition of subjects and traits,
JVCIR(25), No. 1, 2014, pp. 195-206.
Elsevier DOI
Dataset, Gait. Gait recognition

Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.,
HMDB: A large video database for human motion recognition,
Dataset, Action Recognition. The internet has billions of videos, most recognition datasets have a dozen. The dataset itself:
See also HMDB: a large human motion database.

Edinburgh Ceilidh Overhead Video Data,
Dataset, Dance.
WWW Link.
16 ground-truthed dances viewed from overhead, where the 10 dancers follow a structured dance pattern (2 different dances). The dances are in the Scottish Ceilidh style (somewhat similar to American Square Dancing).

Gorelick, L.[Lena], Blank, M.[Moshe], Shechtman, E.[Eli], Irani, M.[Michal], Basri, R.[Ronen],
Actions as Space-Time Shapes,
PAMI(29), No. 12, December 2007, pp. 2247-2253.
Dataset, Actions.
HTML Version.
Earlier: A2, A1, A3, A4, A5: ICCV05(II: 1395-1402).
Human action as 3-D shapes induced by silhouettes in the spacetime volume.

de la Torre-Frade, F.[Fernando], Hodgins, J.K.[Jessica K.], Bargteil, A.W.[Adam W.], Artal, X.M.[Xavier Martin], Macey, J.C.[Justin C.], Collado I Castells, A.[Alexandre], and Beltran, J.[Josep],
Guide to the Carnegie Mellon University Multimodal Activity (CMU-MMAC) Database,
CMU-RI-TR-08-22, April, 2008.
WWW Link. Dataset, Activity Recognition.

Liu, J.[Jun], Shahroudy, A.[Amir], Perez, M.[Mauricio], Wang, G.[Gang], Duan, L.Y.[Ling-Yu], Kot, A.C.[Alex C.],
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding,
PAMI(42), No. 10, October 2020, pp. 2684-2701.
WWW Link. Or:
WWW Link.
Dataset, Human Activity. Benchmark testing, Cameras, Deep learning, Semantics, Lighting, Skeleton, Activity understanding, large-scale benchmark

Shahroudy, A.[Amir], Liu, J., Ng, T.T.[Tian-Tsong], Wang, G.,
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis,
Dataset, Human Activity.

Ji, Y., Yang, Y., Shen, F., Shen, H.T., Zheng, W.S.,
Arbitrary-View Human Action Recognition: A Varying-View RGB-D Action Dataset,
CirSysVideo(31), No. 1, January 2021, pp. 289-300.
Dataset, Action Recognition. Skeleton, Sensors, Videos, Dictionaries, Robots, HRI

FCVID: Fudan-Columbia Video Dataset,

WWW Link. Dataset, Activity Recognition. 90,000+ videos, manually annotated for 239 categories. Human activities.

Ben-Shabat, Y.Z.[Yi-Zhak], Yu, X.[Xin], Saleh, F.[Fatemeh], Campbell, D.[Dylan], Rodriguez-Opazo, C.[Cristian], Li, H.D.[Hong-Dong], Gould, S.[Stephen],
The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose,
WWW Link.
Dataset, Activity Recognition. Deep learning, Annotations, Pose estimation, Object segmentation, Benchmark testing

Corona, K.[Kellie], Osterdahl, K.[Katie], Collins, R.[Roderic], Hoogs, A.[Anthony],
MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection,
Dataset, Activity Detection. Solid modeling, Visualization, Annotations, NIST, Cameras
See also Multiview Extended Video with Activities.

Damen, D.[Dima], Doughty, H.[Hazel], Farinella, G.M.[Giovanni Maria], Fidler, S.[Sanja], Furnari, A.[Antonino], Kazakos, E.[Evangelos], Moltisanti, D.[Davide], Munro, J.[Jonathan], Perrett, T.[Toby], Price, W.[Will], Wray, M.[Michael],
Scaling Egocentric Vision: The Epic Kitchens Dataset,
ECCV18(II: 753-771).
Springer DOI
Dataset, Egocentric Actions.

Edinburgh office monitoring video dataset,
WWW Link. Dataset, Office Monitor.
This dataset consists of video, image frames, and ground truth for 20 days of monitoring people in 4 different offices. The data is acquired using a fixed camera as a set of 1280*720 pixel color images captured at an average of about 1 FPS. This dataset is interesting because there are about 450K labeled frames of people doing standard office activities. The ground truth is the position of each person in each image with a bounding box, plus their behavior. Four behaviors are annotated (standing/walking, sitting, two or three people are talking, or the person in room has fallen). Paper to appear CVPR21.

Zhang, J.[Jing], Li, W.Q.[Wan-Qing], Ogunbona, P.O.[Philip O.], Wang, P.[Pichao], Tang, C.[Chang],
RGB-D-based action recognition datasets: A survey,
PR(60), No. 1, 2016, pp. 86-105.
Elsevier DOI
Dataset, Action Recognition. Action recognition

Laptev, I.[Ivan], Caputo, B.[Barbara], Schuldt, C.[Christian], Lindeberg, T.[Tony],
Local velocity-adapted motion events for spatio-temporal recognition,
CVIU(108), No. 3, December 2007, pp. 207-229.
Elsevier DOI

Earlier: A3, A1, A2, Only:
Recognizing human actions: a local SVM approach,
ICPR04(III: 32-36).
Dataset, Actions.
WWW Link. Motion; Local features; Motion descriptors; Matching; Velocity adaptation; Action recognition; Learning; SVM

Li, W.H.[Wen-Hui], Wong, Y.K.[Yong-Kang], Liu, A.A.[An-An], Li, Y.[Yang], Su, Y.T.[Yu-Ting], Kankanhalli, M.[Mohan],
Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking,
Dataset, Action Recognition.
HTML Version. Multi-Camera Action Dataset (MCAD). Benchmark testing, Cameras, Computer vision, Heuristic algorithms, Internet, Robustness, Surveillance

Barekatain, M., Martí, M., Shih, H.F., Murray, S., Nakayama, K., Matsuo, Y., Prendinger, H.,
Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection,
Dataset, Okutama-Action. Cameras, Data collection, Mobile communication, Surveillance, Training, Video, sequences

Zhao, H., Torralba, A., Torresani, L., Yan, Z.,
HACS: Human Action Clips and Segments Dataset for Recognition and Temporal Localization,
WWW Link. Dataset, Human Actions. image classification, image motion analysis, image segmentation, learning (artificial intelligence), video signal processing, YouTube

Kong, Q., Wu, Z., Deng, Z., Klinkigt, M., Tong, B., Murakami, T.,
MMAct: A Large-Scale Dataset for Cross Modal Human Action Understanding,
Dataset, Human Actions. image colour analysis, image motion analysis, image recognition, video signal processing, RGB videos, Task analysis

Ofli, F., Chaudhry, R., Kurillo, G., Vidal, R., Bajcsy, R.,
Berkeley MHAD: A comprehensive Multimodal Human Action Database,
Dataset, Human Actions.

Vaquette, G., Orcesi, A., Lucat, L., Achard, C.,
The DAily Home LIfe Activity Dataset: A High Semantic Activity Dataset for Online Recognition,
Dataset, Smart Home. Cameras, Databases, Protocols, Semantics, Sensors, Skeleton, Videos

Ragusa, F.[Francesco], Furnari, A.[Antonino], Livatino, S.[Salvatore], Farinella, G.M.[Giovanni Maria],
The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain,
WWW Link.
Dataset, Interactions. Taxonomy, Motorcycles, Object detection, Tools, Object recognition

UDIVA Dataset,
WWW Link. Dataset, Social Interaction. Non-acted datasetof face-to-face dyadic interactions. WACV Paper.
See also Context-Aware Personality Inference in Dyadic Scenarios: Introducing the UDIVA Dataset.

Gong, W.J.[Wen-Juan], Gonzàlez, J.[Jordi], Tavares, J.M.R.S.[João Manuel R.S.], Xavier Roca, F.,
A New Image Dataset on Human Interactions,
Springer DOI
Dataset, Action Recognition.

Burger, S.[Susanne],
The CHIL RT07 Evaluation Data,
Springer DOI
Dataset, Activity Recogniton.

Fouhey, D.F., Kuo, W., Efros, A.A., Malik, J.,
From Lifestyle VLOGs to Everyday Interactions,
Dataset, Action.
HTML Version. Videos, YouTube, Task analysis, Cameras, Internet, Benchmark testing

CVBASE Annotated Video Data,
HTML Version. Dataset, Video.

Olympic Sports Dataset,
WWW Link. Dataset, Sports. The Olympic Sports Dataset contains videos of athletes practicing different sports. We have obtained all video sequences from YouTube and annotated their class label with the help of Amazon Mechanical Turk. Refer to:
See also Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification.

UCF Sports Action Dataset,
WWW Link. Details:
WWW Link. A large set of sports actions. Dataset, Sports. Note that many of the other non UCF links to data on that page are out of date.

LHI Sports Activity Dataset,
Subset of larger dataset. Online2008
HTML Version. Dataset, Sports.
See also Lotus Hill Institute.

MEXaction2 action detection and localization dataset,
WWW Link. Dataset, Actions. The aim of the MEXaction2 dataset is to support the development and evaluation of methods for spotting instances of short actions in a relatively large video database. Actions: BullChargeCape (1324) and HorseRiding (651).

Zhang, W.C.[Wei-Chen], Liu, Z.G.[Zhi-Guang], Zhou, L.Y.[Liu-Yang], Leung, H.[Howard], Chan, A.B.[Antoni B.],
Martial Arts, Dancing and Sports dataset: A challenging stereo and multi-view dataset for 3D human pose estimation,
IVC(61), No. 1, 2017, pp. 22-39.
Elsevier DOI
Dataset, Human Activities. Human pose estimation

Zalluhoglu, C.[Cemil], Ikizler-Cinbis, N.[Nazli],
Collective Sports: A multi-task dataset for collective activity recognition,
IVC(94), 2020, pp. 103870.
Elsevier DOI
Dataset, Sports. Collective activity recognition, Action recognition, Convolutional neural networks, Multi-task learning, LSTM

Setti, F.[Francesco], Conigliaro, D.[Davide], Rota, P.[Paolo], Bassetti, C.[Chiara], Conci, N.[Nicola], Sebe, N.[Nicu], Cristani, M.[Marco],
The S-Hock dataset: A new benchmark for spectator crowd analysis,
CVIU(159), No. 1, 2017, pp. 47-58.
Elsevier DOI
Dataset, Crowd Analysis.
Earlier: A2, A3, A1, A4, A5, A6, A7:
The S-HOCK dataset: Analyzing crowds at the stadium,
Spectator, monitoring

Ali, S.[Saad], Shah, M.[Mubarak],
Floor Fields for Tracking in High Density Crowd Scenes,
ECCV08(II: 1-14).
Springer DOI
PDF File.
Dataset, Tracking.
WWW Link.

Ali, S.[Saad], Shah, M.[Mubarak],
A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis,
PDF File. Dataset, Surveillance. The dataset for this paper is available:
WWW Link. UCF Lists:
WWW Link. But no link to data.

Ali, S.[Saad],
Crowd Flow Segmentation and Stability Analysis,
HTML Version. The more general discussion of the issues of the other papers. Includes a more complete dataset and pointers to other useful code. Dataset, Surveillance.
WWW Link.

Cheng, M.[Ming], Cai, K.[Kunjing], Li, M.[Ming],
RWF-2000: An Open Large Scale Video Database for Violence Detection,
Dataset, Violence. Image motion analysis, Databases, Surveillance, Logic gates, Cameras

Ntalampiras, S.[Stavros], Arsic, D.[Dejan], Hofmann, M.[Martin], Andersson, M.[Maria], Ganchev, T.[Todor],
PROMETHEUS: heterogeneous sensor database in support of research on human behavioral patterns in unrestricted environments,
SIViP(8), No. 7, October 2014, pp. 1211-1231.
Springer DOI
Dataset, Human Activity.

Penate-Sanchez, A.[Adrian], Freire-Obregón, D.[David], Lorenzo-Melián, A.[Adrián], Lorenzo-Navarro, J.[Javier], Castrillón-Santana, M.[Modesto],
TGC20ReId: A dataset for sport event re-identification in the wild,
PRL(138), 2020, pp. 355-361.
Elsevier DOI
Dataset, Sports. Sport, Re-identification, Dataset

Abrams, A.[Austin], Tucek, J.[Jim], Little, J.[Joshua], Jacobs, N.[Nathan], Pless, R.[Robert],
LOST: Longterm Observation of Scenes (with Tracks),
Using the data, same half hour every day. Dataset, Surveillance.

Rebecq, H.[Henri], Ranftl, R.[René], Koltun, V.[Vladlen], Scaramuzza, D.[Davide],
High Speed and High Dynamic Range Video with an Event Camera,
PAMI(43), No. 6, June 2021, pp. 1964-1980.

Events-To-Video: Bringing Modern Computer Vision to Event Cameras,
Code, HDR. Dataset, HDR. Dataset, E2VID.
HTML Version. Image reconstruction, Cameras, Streaming media, Dynamic range, Brightness, Heuristic algorithms, high dynamic range

DAVIS: Densely Annotated VIdeo Segmentation,
WWW Link.
2017. Dataset, Video Segmentation. For the competition at CVPR 2017.

Video Instance Segmentation - YouTube-VOS,
WWW Link.
Dataset, Video Segmentation. Dataset for video instance segmentation.

Video Instance Segmentation - YouTube-VOS,
WWW Link.
Dataset, Video Segmentation. Dataset for video instance segmentation. And related to Youtube-VIS.

Qi, J.Y.[Ji-Yang], Gao, Y.[Yan], Hu, Y.[Yao], Wang, X.G.[Xing-Gang], Liu, X.Y.[Xiao-Yu], Bai, X.[Xiang], Belongie, S.[Serge], Yuille, A.[Alan], Torr, P.H.S.[Philip H.S.], Bai, S.[Song],
OVIS: Occluded Video Instance Segmentation,
Online2021. WWW Link.
Dataset, Video Segmentation. Designed with the philosophy of perceiving object occlusions in videos, which could reveal the complexity and the diversity of real-world scenes.

Perazzi, F.[Federico], Pont-Tuset, J., McWilliams, B., Van Gool, L.J., Gross, M., Sorkine-Hornung, A.[Alexander],
A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation,
Dataset, Video Segmentation.

Change Detection Benchmark Website,
2012 Dataset, Motion Detection.
WWW Link. Dataset for the 2012 Change Detection workshop at CVPR.

Scene Background Initialization (SBI) Dataset,
HTML Version. Dataset, Background.
14 sequences with ground truth.
See also Towards Benchmarking Scene Background Initialization.

Mahmood, M.H.[Muhammad Habib], Díez, Y.[Yago], Salvi, J.[Joaquim], Lladó, X.[Xavier],
A collection of challenging motion segmentation benchmark datasets,
PR(61), No. 1, 2017, pp. 1-14.
Elsevier DOI
Dataset, Motion Segmentation. Motion segmentation

Mahmood, M.H.[Muhammad Habib], Zappella, L.[Luca], Díez, Y.[Yago], Salvi, J.[Joaquim], Lladó, X.[Xavier],
A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15),
Springer DOI
Dataset, Motion Segmentation.

Cuevas, C.[Carlos], Yáñez, E.M.[Eva María], García, N.[Narciso],
Labeled dataset for integral evaluation of moving object detection algorithms: LASIESTA,
CVIU(152), No. 1, 2016, pp. 103-117.
Elsevier DOI
Dataset, Foreground Detection. Database

Vacavant, A.[Antoine], Chateau, T.[Thierry], Wilhelm, A.[Alexis], Lequièvre, L.[Laurent],
A Benchmark Dataset for Outdoor Foreground/Background Extraction,
Springer DOI
Dataset, Foreground Extraction. Surveillance applications.

Image Stitching Database,
HTML Version. Dataset, Image Stitching.

Richter, S.R.[Stephan R.], Hayder, Z.[Zeeshan], Koltun, V.[Vladlen],
Playing for Benchmarks,
Dataset, Video. image annotation, image resolution, image segmentation, image sequences, object detection, object tracking,

Stottinger, J.[Julian], Zambanini, S.[Sebastian], Khan, R.[Rehanullah], Hanbury, A.[Allan],
FeEval A Dataset for Evaluation of Spatio-temporal Local Features,
Dataset, Motion.

Avola, D., Cinque, L., Foresti, G.L., Martinel, N., Pannone, D., Piciarelli, C.,
A UAV Video Dataset for Mosaicking and Change Detection From Low-Altitude Flights,
SMCS(50), No. 6, June 2020, pp. 2139-2149.
Dataset, Change Detection. Video sequences, Change detection algorithms, Cameras, Detection algorithms, Task analysis, Telemetry, unmanned aerial vehicle (UAV)

WWW Link. Dataset, Superresolution. Refer to:
See also Jointly Optimized Regressors for Image Super-resolution.

Set5, Set14, Urban 100, BSD 100, Sun-Hays 80 Datasets,
Dataset, Super Resolution. Linkd from:
WWW Link.

Wang, Y.Q.[Ying-Qian], Wang, L.G.[Long-Guang], Yang, J.G.[Jun-Gang], An, W.[Wei], Guo, Y.L.[Yu-Lan],
Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution,
Dataset, Flickr. Dataset, Super Resolution.
WWW Link. cameras, data acquisition, image resolution, stereo image processing, large-scale stereo dataset, super resolution

Xiao, J.X.[Jian-Xiong], Owens, A.[Andrew], Torralba, A.[Antonio],
SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels,
Dataset, Scene Understanding.
WWW Link. RGB-D Video dataset. Camera pose and object labels. Interactive reconstruction process.

Shugrina, M.[Maria], Liang, Z.H.[Zi-Heng], Kar, A.[Amlan], Li, J.[Jiaman], Singh, A.[Angad], Singh, K.[Karan], Fidler, S.[Sanja],
Creative Flow+ Dataset,
Dataset, Optical Flow.
WWW Link. Video dataset richly labeled with per-pixel optical flow, occlusions, correspondences, segmentation labels, normals, and depth.

Mayer, N.[Nikolaus], Ilg, E.[Eddy], Häusser, P.[Philip], Fischer, P.[Philipp], Cremers, D.[Daniel], Dosovitskiy, A.[Alexey], Brox, T.[Thomas],
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation,
Dataset, Optical Flow.

Baker, S.[Simon], Scharstein, D.[Daniel], Lewis, J.P., Roth, S.[Stefan], Black, M.J.[Michael J.], Szeliski, R.[Richard],
A Database and Evaluation Methodology for Optical Flow,
IJCV(92), No. 1, March 2011, pp. 1-31.
Springer DOI

Earlier: A1, A4, A2, A5, A3, A6: ICCV07(1-8).
Dataset, Optical Flow.
WWW Link.

Nascimento, S.M.C., Ferreira, F., and Foster, D.H.,
Statistics of spatial cone-excitation ratios in natural scenes,
JOSA-A(19), No. 8, August 2002, pp. 1484-1490.
PDF File. Dataset, Hyperspectral.
HTML Version.

Foster, D.H., Nascimento, S.M.C., Amano, K.,
Information limits on neural identification of coloured surfaces in natural scenes,
Visual Neuroscience(21), 2004, pp. 331-336.
PDF File. Dataset, Hyperspectral.
HTML Version.

Bossard, L.[Lukas], Guillaumin, M.[Matthieu], Van Gool, L.J.[Luc J.],
Food-101: Mining Discriminative Components with Random Forests,
ECCV14(VI: 446-461).
Springer DOI
Dataset, Food. 101 food categories, with 101’000 images recognizing pictured dishes.

Wang, X.H.[Xiao-Han], Eliott, F.M.[Fernanda M.], Ainooson, J.[James], Palmer, J.H.[Joshua H.], Kunda, M.[Maithilee],
An Object is Worth Six Thousand Pictures: The Egocentric, Manual, Multi-image (EMMI) Dataset,
WWW Link.
Dataset, Learning. Egocentric, Manual, Multi-Image (EMMI) Dataset. Automobiles, Cameras, Manuals, Object recognition, Toy manufacturing industry, Training, Visualization

Agarwal, S.[Shivani], Awan, A.[Aatif], and Roth, D.[Dan],
Learning to Detect Objects in Images via a Sparse, Part-Based Representation,
PAMI(26), No. 11, November 2004, pp. 1475-1490.
IEEE Abstract. Or:
PDF File.
WWW Link.
Dataset, Vehicles. Detecting specific object classes (e.g. cars).

Borji, A.[Ali], Izadi, S.[Saeed], Itti, L.[Laurent],
iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning,
Dataset, Learning.

300 Videos in the Wild,
2015 Dataset, Faces.
WWW Link. Used for the ICCV 2015 workshop challenge.

WIDER Attribute dataset,
WWW Link. Dataset, Faces.
See also Human Attribute Recognition by Deep Hierarchical Contexts.

Description of the Collection of Facial Images,
2007 Dataset, Faces.
HTML Version. Essex collection of faces. 395 people, 20 images each.

Annotated Facial Dataset,
2007 Dataset, Faces.
WWW Link.

The CMU Multi-PIE Face Database,
2010 Dataset, Faces.
WWW Link. It contains 337 subjects, captured under 15 view points and 19 illumination conditions in four recording sessions for a total of more than 750,000 images.

FaceScrub Annotated Face Dataset,
2014 Dataset, Faces.
HTML Version. 100,000 images of 530 people. Acquired from internet search with rejection of pictures that do not match.
See also data-driven approach to cleaning large face datasets, A.

GVVPerfcapEva Repository of Evaluation Data Sets,
2015 Dataset, Faces. Dataset, Human Motion. Dataset, Hand Tracking.
WWW Link. A set of dataset including:
GVVPerfCapEva: IDT - Full body skeletal motion capture results from from 
 body-worn inertial sensor data and depth camera recordings
GVVPerfCapEva: Dexter 1: Evaluation data set for 3D hand tracking with 
 depth and multi-view video data
GVVPerfCapEva: PDT 2013: Body shape estimation and real-time motion 
 capture with a depth camera
GVVPerfcapEva: BinoCap - Dense 3D full-body performance capture with 
 handheld stereo cameras (single + multiple person(s))
GVVPerfcapEva: MonFacecCap - Monocular dense face performance capture
GVVPerfCapEva: MVIC - markerless multi-view performance capture of 
 multiple interacting characters
GVVPerfCapEva: HKIC: Performance capture of interacting characters with 
 handheld Kinects

MPII Human Shape,
2015 Dataset, Human Pose.
WWW Link. Expressive 3D human body shape models and tools for human shape space building.

UB KinFace Database,
2011 Dataset, Faces.
HTML Version.

Yale Face Database,
Online2006. First is 165 images.
HTML Version. And 5760 single light source images of 10 subjects each seen under 576 viewing conditions
HTML Version. Dataset, Faces.

The University of Oulu Physics-Based Face Database,
2000. 125 different faces each in 16 different camera calibration and illumination conditions.
WWW Link. Dataset, Faces.

The University of Oulu Face Video Database,
WWW Link. Dataset, Faces.

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations,
2004. 9,594 images of 1040 individuals (595 males and 445 females) with varying Pose, Expression, Accessory, and Lighting
HTML Version. Dataset, Faces.

MIT Face Recognition Database,
Online2000 Fi Dataset, Faces.
HTML Version.
HTML Version. First one is small (19X19) images. Second one has training and test data.

The UMIST Face Database,
1998. Face Recognition.
HTML Version. Dataset, Faces.

NIST Mugshot Identification Database,
HTML Version. Dataset, Faces.

IARPA Janus Benchmark A (IJB-A) dataset,
WWW Link. Dataset, Faces.

The ORL Database of Faces,
1992-1994. More recently called the AT&T database.
HTML Version. Dataset, Faces.

PubFig: Public Figures Face Database,
2015 Dataset, Faces.
WWW Link. 58,797 images of 200 people collected from the internet. Refer to:
See also Attribute and simile classifiers for face verification.

Peer, P.[Peter],
CVL Face Database,
Online1999. Dataset, Faces.
HTML Version. 114 people, 7 images each.

POSTECH Face Database,
2001 Dataset, Faces. Dataset, Expressions. Dataset, Gesture.
HTML Version. A variety of datasets for face recognition, expression recognition, gesture recognition, and video surveillance.
See also POSTECH face database (PF07) and performance evaluation, The.

Face Recognition Vendor Test 2006,
WWW Link. Dataset, Faces.
WWW Link. Results in February 2007.

FacePix Database,
WWW Link. Dataset, Faces. 181 poses 1 degree apart plus lighting (direction) changes.
See also Arizona State University.

Jain, V.[Vidit], Learned-Miller, E.G.[Erick G.],
FDDB: Face Detection Data Set and Benchmark,
UMass2010, Technical Report 2010-009.
WWW Link. Dataset, Faces. annotations for 5171 faces in a set of 2845 images. Subset of
See also Labeled faces in the wild: A database for studying face recognition in unconstrained environments.

Huang, G.B., Ramesh, M., Berg, T.L., Learned-Miller, E.G.,
Labeled faces in the wild: A database for studying face recognition in unconstrained environments,
UMass2007, Technical Report 07-49. annotated faces captured from news articles on the web. Dataset, Faces.
WWW Link. Detected using:
See also Robust Real-Time Face Detection.

Phillips, P.J., Moon, H.J., Rizvi, S.A., Rauss, P.J.,
The FERET Evaluation Methodology for Face-Recognition Algorithms,
PAMI(22), No. 10, October 2000, pp. 1090-1104.
IEEE DOI Evaluation, Faces. Dataset, Faces.

Earlier: A1, A2, A4, A3: CVPR97(137-143).
PDF File.
Evaluation; data.

Phillips, P.J.[P. Jonathon], Wechsler, H.[Harry], Huang, J.[Jeffery], Rauss, P.J.[Patrick J.],
The FERET Database and Evaluation Procedure for Face-Recognition Algorithms,
IVC(16), No. 5, April 27 1998, pp. 295-306.
Elsevier DOI
Evaluation, Faces. Dataset, Faces.

The FERET Database,
WWW Link. Dataset, Faces. Old version. For Color --
See also Color FERET Database, The.
See also National Institute of Standards and Technology (NIST) Intelligent Systems Division.

The Color FERET Database,
NISTJanuary 2008.
WWW Link. Dataset, Faces.

Wong, Y.W.[Yee Wan], Ch'ng, S.I.[Sue Inn], Seng, K.P.[Kah Phooi], Ang, L.M.[Li-Minn], Chin, S.W.[Siew Wen], Chew, W.J.[Wei Jen], Lim, K.H.[King Hann],
A new multi-purpose audio-visual UNMC-VIER database with multiple variabilities,
PRL(32), No. 13, 1 October 2011, pp. 1503-1510.
Elsevier DOI
Dataset, Faces. Audio-visual database; Face recognition; Speech recognition; Visual variation

Mavadati, S.M.[S. Mohammad], Mahoor, M.H.[Mohammad H.], Bartlett, K.[Kevin], Trinh, P.[Philip], Cohn, J.F.[Jeffrey F.],
DISFA: A Spontaneous Facial Action Intensity Database,
AffCom(4), No. 2, 2013, pp. 151-160.
Dataset, Facial Action. Databases

Zhang, X.[Xing], Yin, L.J.[Li-Jun], Cohn, J.F.[Jeffrey F.], Canavan, S.[Shaun], Reale, M.[Michael], Horowitz, A.[Andy], Liu, P.[Peng], Girard, J.M.[Jeffrey M.],
BP4D-Spontaneous: a high-resolution spontaneous 3D dynamic facial expression database,
IVC(32), No. 10, 2014, pp. 692-706.
Elsevier DOI

Earlier: A1, A2, A3, A4, A5, A6, A7, Only:
A high-resolution spontaneous 3D dynamic facial expression database,
Dataset, Facial Expressions. emotion recognition 3D facial expression

Yin, L.J.[Li-Jun], Chen, X.C.[Xiao-Chen], Sun, Y.[Yi], Worm, T.[Tony], Reale, M.[Michael],
A high-resolution 3D dynamic facial expression database,
Dataset, Facial Expressions.

Cheema, U.[Usman], Moon, S.[Seungbin],
Sejong face database: A multi-modal disguise face database,
CVIU(208-209), 2021, pp. 103218.
Elsevier DOI
Dataset, Face Recognition. Biometrics, Disguise recognition, Face database, Face recognition, Multi-modal

Poster, D.[Domenick], Thielke, M.[Matthew], Nguyen, R.[Robert], Rajaraman, S.[Srinivasan], Di, X.[Xing], Fondje, C.N.[Cedric Nimpa], Patel, V.M.[Vishal M.], Short, N.J.[Nathaniel J.], Riggan, B.S.[Benjamin S.], Nasrabadi, N.M.[Nasser M.], Hu, S.[Shuowen],
A Large-Scale, Time-Synchronized Visible and Thermal Face Dataset,
PDF File.
Dataset, Face Recognition. Heating systems, Protocols, Thermal lensing, Photothermal effects, Cameras, Thermal analysis, Task analysis

Cao, J., Li, Y., Zhang, Z.,
Celeb-500K: A Large Training Dataset for Face Recognition,
Dataset, Face Recognition. Training, Face, Face recognition, Measurement, Learning systems, Performance gain, Face detection, face recognition, face dataset, convolutional neural networks

Whitelam, C., Taborsky, E., Blanton, A., Maze, B., Adams, J., Miller, T., Kalka, N., Jain, A.K., Duncan, J.A., Allen, K., Cheney, J., Grother, P.,
IARPA Janus Benchmark-B Face Dataset,
Dataset, Faces. Benchmark testing, Face, Face detection, Face recognition, Media, Protocols, Videos
See also IARPA Janus Benchmark A (IJB-A) dataset.

Kemelmacher-Shlizerman, I., Seitz, S.M., Miller, D., Brossard, E.,
The MegaFace Benchmark: 1 Million Faces for Recognition at Scale,
Dataset, Face Recognition.

Guo, Y.D.[Yan-Dong], Zhang, L.[Lei], Hu, Y.X.[Yu-Xiao], He, X.D.[Xiao-Dong], Gao, J.F.[Jian-Feng],
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,
ECCV16(III: 87-102).
Springer DOI
Dataset, Face Recognition.
WWW Link.

Klare, B.F.[Brendan F.], Klein, B.[Ben], Taborsky, E.[Emma], Blanton, A.[Austin], Cheney, J.[Jordan], Allen, K.[Kristen], Grother, P.[Patrick], Mah, A.[Alan], Burge, M.[Mark], Jain, A.K.[Anil K.],
Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A,
Dataset, Face Recognition.

McDuff, D.J.[Daniel J.], el Kaliouby, R.[Rana], Senechal, T.[Thibaud], Amr, M.[May], Cohn, J.F.[Jeffrey F.], Picard, R.W.[Rosalind W.],
Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected 'In-the-Wild',
Dataset, Facial Expressions. Facial expressions;computer vision;dataset

Toderici, G.[George], Evangelopoulos, G.[Georgios], Fang, T.H.[Tian-Hong], Theoharis, T.[Theoharis], Kakadiaris, I.A.[Ioannis A.],
UHDB11 Database for 3D-2D Face Recognition,
Springer DOI
Dataset, Faces.

Colombo, A.[Alessandro], Cusano, C.[Claudio], Schettini, R.[Raimondo],
UMB-DB: A database of partially occluded 3D faces,
Dataset, Faces.

Somanath, G.[Gowri], Rohith, M.V., Kambhamettu, C.[Chandra],
VADANA: A dense dataset for facial image analysis,
Dataset, Faces.

Özcan, M.[Mert], Jie, L.[Luo], Ferrari, V.[Vittorio], Caputo, B.[Barbara],
A Large-Scale Database of Images and Captions for Automatic Face Naming,
HTML Version.
Dataset, Faces.

Gupta, S.[Shalini], Castleman, K.R.[Kenneth R.], Markey, M.K.[Mia K.], Bovik, A.C.[Alan C.],
Texas 3D Face Recognition Database,
Dataset, Faces.

Bastanfard, A.[Azam], Nik, M.A.[Melika Abbasian], Dehshibi, M.M.[Mohammad Mahdi],
Iranian Face Database with age, pose and expression,
Dataset, Faces.

Denes, L.J., Metes, P., Liu, Y.,
Hyperspectral Face Database,
CMU-RI-TR-02-25, October, 2002.
WWW Link.
Dataset, Faces.

Kärkkäinen, K.[Kimmo], Joo, J.[Jungseock],
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation,
Dataset, Face Recognition.
WWW Link. Training, Social networking (online), Computational modeling, Multimedia Web sites, Decision making, Media

Face Recogniton Home Page,
WWW Link. Code, Face Recognition. Dataset, Faces. Listing of research groups, databases, and vendors.

Face Detection Home Page,
WWW Link. Code, Face Detection. Dataset, Faces. Listing of research groups, databases, and vendors.

BioID Face Database,
2006. Dataset, Faces.
WWW Link.
See also HumanScan, BioID.

Mian, A.S.[Ajmal S.], Bennamoun, M.[Mohammed], Owens, R.A.[Robyn A.],
Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes,
PAMI(28), No. 10, October 2006, pp. 1584-1601.
Dataset, 3-D Data.
HTML Version. And
HTML Version.
3D Recognition and Segmentation of Objects in Cluttered Scenes,
WACV05(I: 8-13).

Region-based Matching for Robust 3D Face Recognition,
HTML Version.

Matching Tensors for Pose Invariant Automatic 3D Face Recognition,
SafeSecur05(III: 120-120).

Performance analysis of an improved tensor based correspondence algorithm for automatic 3d modeling,
ICIP04(III: 1951-1954).

Matching Tensors for Automatic Correspondence and Registration,
ECCV04(Vol II: 495-505).
Springer DOI
Model range data with tensors. Match stored tensor representations.

Min, R.[Rui], Kose, N., Dugelay, J.L.,
KinectFaceDB: A Kinect Database for Face Recognition,
SMCS(44), No. 11, November 2014, pp. 1534-1548.
Dataset, Faces, 3-D. face recognition

Equinox: Human Identification at a Distance,
HID. 2006. IR images available. Face Recognition.
HTML Version. Dataset, Faces.
See also Equinox Corporation.

Moschoglou, S., Papaioannou, A., Sagonas, C., Deng, J.K.[Jian-Kang], Kotsia, I., Zafeiriou, S.P.[Stefanos P.],
AgeDB: The First Manually Collected, In-the-Wild Age Database,
Dataset, Face Age. Computer vision, Databases, Estimation, Face, Face recognition, Machine learning, Protocols

Jalal, A.[Ahsan], Tariq, U.[Usman],
The LFW-Gender Dataset,
CV4AC16(III: 531-540).
Springer DOI
Dataset, Gender.

Dago-Casas, P.[Pablo], Gonzalez-Jimenez, D.[Daniel], Yu, L.L.[Long Long], Alba-Castro, J.L.[Jose Luis],
Single- and cross- database benchmarks for gender classification under unconstrained settings,
Dataset, Faces.

Yang, S.[Shuo], Luo, P.[Ping], Loy, C.C.[Chen Change], Tang, X.[Xiaoou],
Faceness-Net: Face Detection through Deep Facial Part Responses,
PAMI(40), No. 8, August 2018, pp. 1845-1859.
Detectors, Face, Face detection, Mouth, Neural networks, Proposals, Training, Face detection, convolutional neural network, deep learning
WIDER FACE: A Face Detection Benchmark,
Dataset, Face Detection.
From Facial Parts Responses to Face Detection: A Deep Learning Approach,
Detectors; Face; Face detection; Hair; Mouth; Nose; Proposals

Kostinger, M.[Martin], Wohlhart, P.[Paul], Roth, P.M.[Peter M.], Bischof, H.[Horst],
Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization,
Dataset, Faces, Features.

Schneiderman, H.[Henry], Kanade, T.[Takeo],
A Statistical Method for 3D Object Detection Applied to Faces and Cars,
CVPR00(I: 746-751).

A Histogram-based Method for Detection of Faces and Cars,
ICIP00(Vol III: 504-507).

Frontal Face Images,
WWW Link. Dataset, Faces. Combined CMU MIT face dataset.

CMU Profile Face Images,
HTML Version. Dataset, Faces.

Frejlichowski, D.[Dariusz], Tyszkiewicz, N.[Natalia],
The West Pomeranian University of Technology Ear Database: A Tool for Testing Biometric Algorithms,
ICIAR10(II: 227-234).
Springer DOI
Dataset, Biometrics.

O'Toole, A.J.[Alice J.], Harms, J.[Joshua], Snow, S.L.[Sarah L.], Hurst, D.R.[Dawn R.], Pappas, M.R.[Matthew R.], Ayyad, J.H.[Janet H.], Abdi, H.[Herve],
A Video Database of Moving Faces and People,
PAMI(27), No. 5, May 2005, pp. 812-816.
IEEE Abstract.
Dataset, Faces. Face database.

Pandey, P.[Prashant], Tyagi, A.K.[Aayush Kumar], Ambekar, S.[Sameer], Prathosh, A.P.,
Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images Through Generative Latent Search,
Springer DOI
Dataset, Segmentation.
WWW Link.

Gu, Q., Wang, G., Chiu, M.T., Tai, Y., Tang, C.,
LADN: Local Adversarial Disentangling Network for Facial Makeup and De-Makeup,
Dataset, Faces.
WWW Link. face recognition, feature extraction, LADN, local adversarial disentangling network, facial makeup, Mouth

Li, S.Z.[Stan Z.], Yi, D.[Dong], Lei, Z.[Zhen], Liao, S.C.[Sheng-Cai],
The CASIA NIR-VIS 2.0 Face Database,
Dataset, Face Recognition. IR dataset.

Dynamic 2D/3D Speaking Face Dataset with Synchronized Audio,
HTML Version. Dataset, Lip Reading. Refer to:
See also 3D Visual passcode: Speech-driven 3D facial dynamics for behaviometrics.

Language Independent Lip Reading,
HTML Version. Dataset, Lip Reading.

OuluVS database,
WWW Link. Dataset, Lip Reading.

Berga, D., Vidal, X.R.F., Otazu, X., Pardo, X.M.,
SID4VAM: A Benchmark Dataset With Synthetic Images for Visual Attention Modeling,
Dataset, Gaze Tracking. gaze tracking, learning (artificial intelligence), neural nets, SID4VAM, visual attention modeling, saliency metrics, Benchmark testing

He, Q.H.[Qiu-Hai], Hong, X.P.[Xiao-Peng], Chai, X.J.[Xiu-Juan], Holappa, J.[Jukka], Zhao, G.Y.[Guo-Ying], Chen, X.L.[Xi-Lin], Pietikäinen, M.[Matti],
OMEG: Oulu Multi-Pose Eye Gaze Dataset,
Springer DOI
Dataset, Gaze.

Hadizadeh, H., Enriquez, M.J., Bajic, I.V.,
Eye-Tracking Database for a Set of Standard Video Sequences,
IP(21), No. 2, February 2012, pp. 898-903.
Dataset, Eye Tracking.

Fox, N.A.[Niall A.], O'Mullane, B.A.[Brian A.], Reilly, R.B.[Richard B.],
VALID: A New Practical Audio-Visual Database, and Comparative Results,
Springer DOI
WWW Link.
Dataset, Faces.

Sharma, P.[Prag], Reilly, R.B.[Richard B.],
The UCD Colour Face Image Database for Face Detection,
WWW Link. Dataset, Faces.

Mollahosseini, A., Hasani, B., Mahoor, M.H.,
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild,
AffCom(10), No. 1, January 2019, pp. 18-31.
Dataset, Facial Expressions. Databases, Computational modeling, Face, Face recognition, Affective computing, Magnetic heads, arousal

CMU Facial Expression Database,
1999 Dataset, Faces. Dataset, Facial Expression.
HTML Version. Includes annotation.

Matuszewski, B.J.[Bogdan J.], Quan, W.[Wei], Shark, L.K.[Lik-Kwan],
High-resolution comprehensive 3-D dynamic database for facial articulation analysis,
Dataset, Facial Expressions.

Lucey, P.[Patrick], Cohn, J.F.[Jeffrey F.], Prkachin, K.M.[Kenneth M.], Solomon, P.E.[Patricia E.], Matthews, I.[Iain],
Painful data: The UNBC-McMaster shoulder pain expression archive database,
Dataset, Facial Expression.

Children Spontaneous Facial Expression Video Database (LIRIS-CSE),
2019. Dataset, Facial Expressions.
WWW Link. spontaneous / natural facial expressions of 12 children in diverse settings with variable recording scenarios showing six universal or prototypic emotional expressions (happiness, sadness, anger, surprise, disgust and fear).
See also novel database of children's spontaneous facial expressions (LIRIS-CSE), A.

McDuff, D.J.[Daniel J.], Amr, M., el Kaliouby, R.[Rana],
AM-FED+: An Extended Dataset of Naturalistic Facial Expressions Collected in Everyday Settings,
AffCom(10), No. 1, January 2019, pp. 7-17.
Dataset, Facial Expressions. Videos, Encoding, Face recognition, Training, Lighting, Task analysis, Databases, Facial expressions, facial action coding system, corpora

Yan, W.J.[Wen-Jing], Wu, Q.[Qi], Liu, Y.J.[Yong-Jin], Wang, S.J.[Su-Jing], Fu, X.L.[Xiao-Lan],
CASME database: A dataset of spontaneous micro-expressions collected from neutralized faces,
Dataset, Facial Expressions. computer vision

Lyons, M.J., Akamatsu, S., Kamachi, M., Gyoba, J.,
Coding Facial Expressions with Gabor Wavelets,
IEEE DOI Dataset, Facial Expressions.
HTML Version. 213 images of 7 facial expressions, 10 Japanese female subjects.

Oulu-CASIA NIR&VIS facial expression database,
WWW Link. Dataset, Facial Expressions. 6 typical expressions from 80 subjects.

BU-3DFE (Binghamton University 3D Facial Expression) Database,
Dataset, Facial Expressions.
HTML Version.

The AR Face Database,
HTML Version. Or:
HTML Version. Dataset, Faces.

Sim, T.[Terence], Baker, S., Bsat, M.,
The CMU Pose, Illumination, and Expression Database,
PAMI(25), No. 12, December 2003, pp. 1615-1618.
IEEE Abstract.
Dataset, Faces.
The CMU Pose, Illumination, and Expression (PIE) Database of Human Faces,
HTML Version.

And: CMU-RI-TR-01-02, January, 2001.
HTML Version.
PDF File.
PS File.
HTML Version.

Gross, R.[Ralph], Matthews, I.[Iain], Cohn, J.F.[Jeffrey F.], Kanade, T.[Takeo], Baker, S.[Simon],
IVC(28), No. 5, May 2010, pp. 807-813.
Elsevier DOI
Dataset, Faces.
Earlier: FG08(1-8).
Face database; Face recognition across pose; Face recognition across illumination; Face recognition across expression
See also CMU Pose, Illumination, and Expression Database, The.

Kanade, T.[Takeo], Cohn, J.F.[Jeffrey F.], Tian, Y.L.[Ying-Li],
Comprehensive Database for Facial Expression Analysis,
Dataset, Faces. Dataset, Expressions.

Wang, S., Liu, Z., Lv, S., Lv, Y., Wu, G., Peng, P., Chen, F., Wang, X.,
A Natural Visible and Infrared Facial Expression Database for Expression Recognition and Emotion Inference,
MultMed(12), No. 7, 2010, pp. 682-691.
Dataset, Facial Expressions.

Matuszewski, B.J.[Bogdan J.], Quan, W.[Wei], Shark, L.K.[Lik-Kwan], McLoughlin, A.S.[Alison S.], Lightbody, C.E.[Catherine E.], Emsley, H.C.A.[Hedley C.A.], Watkins, C.L.[Caroline L.],
Hi4D-ADSIP 3-D dynamic facial articulation database,
IVC(30), No. 10, October 2012, pp. 713-727.
Elsevier DOI
Dataset, Facial Expressions. Facial articulation database; Expression recognition; Facial; Dysfunctions; Facial expression validation

Wang, S.F.[Shang-Fei], Liu, Z.L.[Zhi-Lei], Wang, Z.Y.[Zhao-Yu], Wu, G.B.[Guo-Bing], Shen, P.J.[Pei-Jia], He, S.[Shan], Wang, X.[Xufa],
Analyses of a Multimodal Spontaneous Facial Expression Database,
AffCom(4), No. 1, January 2013, pp. 34-46.
Dataset, Expression Recognition.

Baveye, Y., Dellandrea, E., Chamaret, C., Chen, L.M.[Li-Ming],
LIRIS-ACCEDE: A Video Database for Affective Content Analysis,
AffCom(6), No. 1, January 2015, pp. 43-55.
Dataset, Affective. copyright

Kossaifi, J.[Jean], Walecki, R.[Robert], Panagakis, Y.[Yannis], Shen, J.[Jie], Schmitt, M.[Maximilian], Ringeval, F.[Fabien], Han, J.[Jing], Pandit, V.[Vedhas], Toisoul, A.[Antoine], Schuller, B.[Björn], Star, K.[Kam], Hajiyev, E.[Elnar], Pantic, M.[Maja],
SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild,
PAMI(43), No. 3, March 2021, pp. 1022-1040.
Dataset, Emotion. Databases, Tools, Computational modeling, Biological system modeling, Sensors, Affective computing, facial action units

Zhang, Z., Girard, J.M., Wu, Y., Zhang, X., Liu, P., Ciftci, U., Canavan, S., Reale, M., Horowitz, A., Yang, H., Cohn, J.F., Ji, Q., Yin, L.,
Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis,
Dataset, Emotion.

Aubrey, A.J.[Andrew J.], Marshall, D.[David], Rosin, P.L.[Paul L.], Vendeventer, J.[Jason], Cunningham, D.W.[Douglas W.], Wallraven, C.[Christian],
Cardiff Conversation Database (CCDb): A Database of Natural Dyadic Conversations,
Dataset, Facial Expressions. Conversations; Database; Facial Expressions

Lucey, P.[Patrick], Cohn, J.F.[Jeffrey F.], Kanade, T.[Takeo], Saragih, J.M.[Jason M.], Ambadar, Z.[Zara], Matthews, I.[Iain],
The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression,
Dataset, Facial Expressions.

Sapinski, T.[Tomasz], Kaminska, D.[Dorota], Pelikant, A.[Adam], Ozcinar, C.[Cagri], Avots, E.[Egils], Anbarjafari, G.[Gholamreza],
Multimodal Database of Emotional Speech, Video and Gestures,
Springer DOI
Dataset, Emotions.

Sneddon, I., McRorie, M., McKeown, G., Hanratty, J.,
The Belfast Induced Natural Emotion Database,
AffCom(3), No. 1, 2012, pp. 32-41.
Dataset, Emotions.

Wei, H.L.[Hao-Lin], Monaghan, D.S.[David S.], O'Connor, N.E.[Noel E.], Scanlon, P.[Patricia],
A New Multi-modal Dataset for Human Affect Analysis,
Springer DOI
Dataset, Human Affect.

Petridis, S.[Stavros], Martinez, B.[Brais], Pantic, M.[Maja],
The MAHNOB Laughter database,
IVC(31), No. 2, February 2013, pp. 186-202.
Elsevier DOI
Dataset, Laughter. Laughter; Audiovisual; Thermal; Database; Audiovisual automatic laughter-speech discrimination

Abadi, M.K., Subramanian, R., Kia, S.M., Avesani, P., Patras, I., Sebe, N.,
DECAF: MEG-Based Multimodal Database for Decoding Affective Physiological Responses,
AffCom(6), No. 3, July 2015, pp. 209-222.
Dataset, Affective Responses. Databases

Provost, E.M., Shangguan, Y., Busso, C.,
UMEME: University of Michigan Emotional McGurk Effect Data Set,
AffCom(6), No. 4, October 2015, pp. 395-409.
Dataset, Emotion Recognition. Emotion recognition

Yan, J.J.[Jing-Jie], Wang, B.[Bei], Liang, R.[Ruiyu],
A Novel Bimodal Emotion Database from Physiological Signals and Facial Expression,
IEICE(E101-D), No. 7, July 2018, pp. 1976-1979.
WWW Link.
Dataset, Emotions.

Lee, J.Y.[Ji-Young], Kim, S.R.[Seung-Ryong], Kim, S.[Sunok], Park, J.[Jungin], Sohn, K.H.[Kwang-Hoon],
Context-Aware Emotion Recognition Networks,
Dataset, Emotion Recognition.
WWW Link. emotion recognition, face recognition, feature extraction, image fusion, neural nets, visual scene, boosting manner, Adaptive systems

Vicol, P.[Paul], Tapaswi, M.[Makarand], Castrejón, L.[Lluís], Fidler, S.[Sanja],
MovieGraphs: Towards Understanding Human-Centric Situations from Videos,
WWW Link. Dataset, Gestures. Videos of social situations to teach robots to understand people. Videos, Motion pictures, Semantics, Natural languages, Face, Automobiles, Legged locomotion

Nguyen, H.[Hung], Kotani, K.[Kazunori], Chen, F.[Fan], Le, B.[Bac],
A Thermal Facial Emotion Database and Its Analysis,
Springer DOI
Dataset, Facial Expression.

Miranda-Correa, J.A.[Juan Abdon], Abadi, M.K.[Mojtaba Khomami], Sebe, N.[Nicu], Patras, I.[Ioannis],
AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups,
AffCom(12), No. 2, April 2021, pp. 479-493.
Dataset, Emotion. Videos, Databases, Mood, Physiology, Electroencephalography, Brain modeling, Electrocardiography, Emotion classification, EEG, affective computing

VGG Pose Datasets,
2013 Dataset, Human Pose.
HTML Version. A collection of several human pose datasets, BBC Pose, YouTube Pose, ChaLearn Pose.

Verma, M., Kumawat, S., Nakashima, Y., Raman, S.,
Yoga-82: A New Dataset for Fine-grained Classification of Human Poses,
Dataset, Homan Pose. Legged locomotion, Wheels, Pose estimation, Computer vision, Visualization, Skeleton, Image resolution

Bourdev, L.[Lubomir], and Malik, J.[Jitendra],
H3D Dataset,
2009. Dataset, Humans.
WWW Link. Annotated human images.

Nibali, A.[Aiden], Millward, J.[Joshua], He, Z.[Zhen], Morgan, S.[Stuart],
ASPset: An outdoor sports pose video dataset with 3D keypoint annotations,
IVC(111), 2021, pp. 104196.
Elsevier DOI
Dataset, Human Pose. Markerless motion capture, Human pose estimation, Triangulation, Camera calibration

van der Aa, N.P., Luo, X., Giezeman, G.J., Tan, R.T., Veltkamp, R.C.,
UMPM benchmark: A multi-person dataset with synchronized video and motion capture data for evaluation of articulated human motion and interaction,
Dataset, Human Pose.

HandNet Hand Images,
2015 Dataset, Gestures.
WWW Link.
More than 214971 images of 10 different particpants' hands captured by a RealSense RGBD sensor performing random articulations. Annotations include: per pixel classes, 6D fingertip pose, heatmap. Recorded at GIP Lab, Technion.

Fanelli, G., Gall, J., Romsdorfer, H., Weise, T., Van Gool, L.J.,
A 3-D Audio-Visual Corpus of Affective Communication,
MultMed(12), No. 6, 2010, pp. 591-598.
Dataset, Gestures.

Molina, J.[Javier], Pajuelo, J.A.[José A.], Escudero-Viñolo, M.[Marcos], Bescós, J.[Jesús], Martínez, J.M.[José M.],
A natural and synthetic corpus for benchmarking of hand gesture recognition systems,
MVA(25), No. 4, May 2014, pp. 943-954.
Springer DOI
Dataset, Hand Gestures.

Guyon, I.[Isabelle], Athitsos, V.[Vassilis], Jangyodsuk, P.[Pat], Escalante, H.J.[Hugo Jair],
The ChaLearn gesture dataset (CGD 2011),
MVA(25), No. 8, November 2014, pp. 1929-1951.
Springer DOI
Dataset, Gesture.

Materzynska, J., Berger, G., Bax, I., Memisevic, R.,
The Jester Dataset: A Large-Scale Video Dataset of Human Gestures,
Dataset, Gestures. convolutional neural nets, gesture recognition, human computer interaction, video signal processing, deep learning

Moon, G.[Gyeongsik], Yu, S.I.[Shoou-I], Wen, H.[He], Shiratori, T.[Takaaki], Lee, K.M.[Kyoung Mu],
Interhand2.6m: A Dataset and Baseline for 3d Interacting Hand Pose Estimation from a Single RGB Image,
Springer DOI
Dataset, Hand Pose.

Myanganbayar, B.[Battushig], Mata, C.[Cristina], Dekel, G.[Gil], Katz, B.[Boris], Ben-Yosef, G.[Guy], Barbu, A.[Andrei],
Partially Occluded Hands: A Challenging New Dataset for Single-Image Hand Pose Estimation,
Springer DOI
Dataset, Hand Pose.
WWW Link.

Bloom, V.[Victoria], Argyriou, V.[Vasileios], Makris, D.[Dimitrios],
Linear latent low dimensional space for online early action recognition and prediction,
PR(72), No. 1, 2017, pp. 532-547.
Elsevier DOI

Earlier: A1, A3, A2:
G3D: A gaming action dataset and real time action recognition evaluation framework,
Dataset, Gesture Recognition. Action, recognition

Buehler, P.[Patrick], Everingham, M.R.[Mark R.], Huttenlocher, D.P.[Daniel P.], Zisserman, A.[Andrew],
Upper Body Detection and Tracking in Extended Signing Sequences,
IJCV(95), No. 2, November 2011, pp. 180-197.
WWW Link.

Long Term Arm and Hand Tracking for Continuous Sign Language TV Broadcasts,
PDF File.
PDF File. Data available. Dataset, Sign Language.
HTML Version.

The BANCA Database,
WWW Link. Dataset, Biometrics.

Soft-Biometric in Surveillance (SoBiS) Dataset,
WWW Link. Dataset, Biometrics. Recorded at Fraunhofer IOSB.

Ortega-Garcia, J., Fierrez-Aguilar, J., Simon, D., Gonzalez, J., Faundez-Zanuy, M., Espinosa, V., Satue, A., Hernaez, I., Igarza, J.J., Vivaracho, C., Escudero, D., Moro, Q.I.,
MCYT baseline corpus: a bimodal biometric database,
VISP(150), No. 6, December 2003, pp. 395-401.
IEEE Abstract.
Dataset, Biometrics.

Fierrez-Aguilar, J.[Julian], Ortega-Garcia, J.[Javier], Toledano, D.T.[Doroteo Torre], Gonzalez-Rodriguez, J.[Joaquin],
Biosec baseline corpus: A multimodal biometric database,
PR(40), No. 4, April 2007, pp. 1389-1392.
Elsevier DOI
Dataset, Biometrics. Multimodal; Biometrics; Authentication; Verification; Database; Performance; Fingerprint; Iris; Face; Voice

Ortega-Garcia, J.[Javier], Fierrez, J.[Julian], Alonso-Fernandez, F.[Fernando], Galbally, J.[Javier], Freire, M.R.[Manuel R.], Gonzalez-Rodriguez, J.[Joaquin], Garcia-Mateo, C.[Carmen], Alba-Castro, J.L.[Jose-Luis], Gonzalez-Agulla, E.[Elisardo], Otero-Muras, E.[Enrique], Garcia-Salicetti, S.[Sonia], Allano, L.[Lorene], Ly-Van, B.[Bao], Dorizzi, B.[Bernadette], Kittler, J.V.[Josef V.], Bourlai, T.[Thirimachos], Poh, N.[Norman], Deravi, F.[Farzin], Ng, M.N.R.[Ming N. R.], Fairhurst, M.C.[Michael C.], Hennebert, J.[Jean], Humm, A.[Andreas], Tistarelli, M.[Massimo], Brodo, L.[Linda], Richiardi, J.[Jonas], Drygajlo, A.[Andrezj], Ganster, H.[Harald], Sukno, F.M.[Federico M.], Pavani, S.K.[Sri-Kaushik], Frangi, A.[Alejandro], Akarun, L.[Lale], Savran, A.[Arman],
The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB),
PAMI(32), No. 6, June 2010, pp. 1097-1111.
Dataset, Biometrics. Withing the Europens BioSecure framework. 600 individuals. Acquired over internet, in office, and indoor/outdoor with portable hardware. Audio/Video data, signature, fingerprint.

Santos, G., Fiadeiro, P.T., Proença, H.,
BioHDD: a dataset for studying biometric identification on heavily degraded data,
IET-Bio(4), No. 1, 2015, pp. 1-9.
DOI Link
Dataset, Biometrics. biometrics (access control)

Zhang, Y.H.[Yuan-Han], Yin, Z.F.[Zhen-Fei], Li, Y.D.[Yi-Dong], Yin, G.J.[Guo-Jun], Yan, J.J.[Jun-Jie], Shao, J.[Jing], Liu, Z.[Ziwei],
Celeba-Spoof: Large-scale Face Anti-spoofing Dataset with Rich Annotations,
ECCV20(XII: 70-85).
Springer DOI
Dataset, Face Anti-Spoofing.

Oliveira, H.P.[Hélder P.], Magalhães, F.[Filipe],
Two Unconstrained Biometric Databases,
ICIAR12(II: 11-19).
Springer DOI
Dataset, Biometrics.

Zafeiriou, S.P.[Stefanos P.], Hansen, M.[Mark], Atkinson, G.A.[Gary A.], Argyriou, V.[Vasileios], Petrou, M.[Maria], Smith, M.L.[Melvyn L.], Smith, L.N.[Lyndon N.],
The Photoface database,
Dataset, Faces.

Nizami, H., Adkins-Hill, J.P., Zhang, Y.[Yong], Sullins, J.R., McCullough, C., Canavan, S., Yin, L.J.[Li-Jun],
A biometric database with rotating head videos and hand-drawn face sketches,
Dataset, Biometrics.

Li, S.Z.[Stan Z.], Lei, Z.[Zhen], Ao, M.[Meng],
The HFB Face Database for Heterogeneous Face Biometrics research,
Dataset, Faces.

Martinho-Corbishley, D., Nixon, M.S.[Mark S.], Carter, J.N.[John N.],
Soft Biometric Retrieval to Describe and Identify Surveillance Images,
IEEE DOI Dataset, Soft Biometrics. SoBiR Dataset
WWW Link.

Messer, K., Matas, J.G., Kittler, J.V., Luettin, J., Maitre, G.,
XM2VTSDB: The Extended M2VTS Database,
WWW Link. Dataset, Biometrics. 4 versions of 295 subjects.

Donida Labati, R., Genovese, A.[Angelo], Piuri, V.[Vincenzo], Scotti, F.[Fabio], Vishwakarma, S.[Sarvesh],
I-SOCIAL-DB: A labeled database of images collected from websites and social media for Iris recognition,
IVC(105), 2021, pp. 104058.
Elsevier DOI
Dataset, Iris. Biometrics, Iris, Web images

UBIRIS database,
2007, Department of Computer Science, University of Beira Interior, Portugal.
WWW Link. Dataset, Iris Images. The enhanced version is available only for the Iris Segmentation Contest. 241 subjects, 1877 images.

CASIA Iris Image Database,
2007, Chinese Academy of Sciences.
HTML Version. Dataset, Iris Images. Various versions. Version 3. 60 subjects, 2400 images.

NIST ICE Iris Image Database,
2007, NIST.
WWW Link. Dataset, Iris Images. 132 subjects, 2953 images. For most recent info:
See also NIST IREX, Iris Exchange Datasets. and also
See also Iris Recognition Database.

Iris Recognition Database,
HTML Version. Dataset, Iris Images. Derived from University of Bath
See also University of of Bath. in association with Smart Sensors Ltd.
See also Smart Sensors Limited. High resolution images, 20 each eye for 800 people.

Iris Recognition Database,
HTML Version. Dataset, Iris Images. ND-IRIS-0405. A superset of ICE2005 and ICE2006 datasets. (
See also NIST ICE Iris Image Database. ) 64,980 iris images from 712 irises of 356 human subjects. From the Notre Dame group.
See also University of Notre Dame. For more updates:
See also NIST IREX, Iris Exchange Datasets.

UTIRIS: University of Tehran IRIS Image Repository,
WWW Link. Dataset, Iris Images.
Visible and Infrared.

NIST IREX, Iris Exchange Datasets,
WWW Link. Dataset, Iris.
See also Iris Recognition Database.

Dobeš, M.[Michal], and Machala, L.[Libor],
Iris Database,
WWW Link. Dataset, Iris Images. The database used for:
See also Human eye localization using the modified Hough transform.
See also Human Eye Iris Recognition Using the Mutual Information.

Proenca, H.[Hugo], Filipe, S.[Silvio], Santos, R.[Ricardo], Oliveira, J.[Joao], Alexandre, L.A.[Luis A.],
The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance,
PAMI(32), No. 8, August 2010, pp. 1529-1535.
Dataset, Iris Recognition.
WWW Link. Visible wavelength, 4-8 meters distance, people moving.

Omelina, L.[Lubos], Goga, J.[Jozef], Pavlovicova, J.[Jarmila], Oravec, M.[Milos], Jansen, B.[Bart],
A survey of iris datasets,
IVC(108), 2021, pp. 104109.
Elsevier DOI
Survey, Iris Reognition. Dataset, Iris Recognition. Biometrics, Iris recognition, Iris datasets, Human iris

Petrovska-Delacretaz, D., Lelandais, S., Colineau, J., Chen, L.M., Dorizzi, B., Ardabilian, M., Krichen, E., Mellakh, M.A., Chaari, A., Guerfi, S., d'Hose, J., Ben Amor, B.[Boulbaba],
The IV2 Multimodal Biometric Database (Including Iris, 2D, 3D, Stereoscopic, and Talking Face Data), and the IV2-2007 Evaluation Campaign,
Dataset, Iris Recognition.

Maltoni, D.[Davide], Maio, D.[Dario], Jain, A.K.[Anil K.], Prabhakar, S.[Salil],
Handbook of Fingerprint Recognition,
Springer2009. ISBN: 978-1-84882-253-5 Second Edition.
WWW Link.

Earlier: Springer-VerlagNew York, 2003
WWW Link. Survey, Fingerprints. Dataset, Fingerprints. The new edition is greatly expanded. Algorithms, evaluations, sensors, standards, security. Buy this book: Handbook of Fingerprint Recognition

Maio, D., Maltoni, D.[Davide], Cappelli, R.[Raffaele], Wayman, J.L., Jain, A.K.,
FVC2000: Fingerprint Verification Competition,
PAMI(24), No. 3, March 2002, pp. 402-412.
Dataset, Fingerprints.
Invited Paper: FVC2000: Fingerprint Verification Competition,
ICPR00(Vol IV: No paper).

Wilson, C.L., Watson, C.I.,
NIST Special Database 4, Fingerprint Database,
NISTIRMarch 1992.
WWW Link. Dataset, Fingerprints.

Wang, Q., Li, S.Y.,
Database of human segmented images and its application in boundary detection,
IET-IPR(6), No. 3, 2012, pp. 222-229.
DOI Link
Dataset, Segmentation.

ADE20K Dataset,
2017. Dataset, Segmentation.
WWW Link. Annotated data,

LHI Segmentation Dataset,
Subset of larger dataset. Online2008
HTML Version. Dataset, Segmentation.
See also Lotus Hill Institute.

The PASCAL Visual Object Classes Challenge 2012,
Online2012 Dataset, Segmentation.
WWW Link. Various PASCAL datasets for different years
See also Pascal: Pattern Analysis, Statistical Modelling and Computational Learning.

COCO: Common Objects in Context,
Online Dataset, Segmentation.
WWW Link. Large-scale object detection, segmentation, and captioning dataset. Used for ECCV 2018 challange:
HTML Version.

Barnard, K.[Kobus], Fan, Q.F.[Quan-Fu], Swaminathan, R.[Ranjini], Hoogs, A.[Anthony], Collins, R.[Roderic], Rondot, P.[Pascale], Kaufhold, J.[John],
Evaluation of Localized Semantics: Data, Methodology, and Experiments,
IJCV(77), No. 1-3, May 2008, pp. 199-217.
Springer DOI
Dataset, Segmentation. Dataset with hand segmentations.
WWW Link.

Follmann, P.[Patrick], Böttger, T.[Tobias], Härtinger, P.[Philipp], König, R.[Rebecca], Ulrich, M.[Markus],
MVTec D2S: Densely Segmented Supermarket Dataset,
ECCV18(X: 581-597).
Springer DOI
Dataset, Segmentation.

Kampel, M.[Martin], Hanbury, A.[Allan], Blauensteiner, P.[Philipp], Wildenauer, H.[Horst],
Improved motion segmentation based on shadow detection,
ELCVIA(6), No. 3, December 2007, pp. 1-12.
DOI Link
Includes Test Data: Dataset, Shadow Detection.

Semantic Boundaries Dataset and Benchmark,
Online2011. Dataset, Segmentation.
HTML Version. or:
HTML Version.
See also Semantic contours from inverse detectors. Related to:
See also Berkeley Segmentation Dataset and Benchmark, The.
See also PASCAL Visual Object Classes Challenge 2012, The.

Arbelaez, P.[Pablo], Fowlkes, C.C.[Charless C.], and Martin, D.R.[David R.],
The Berkeley Segmentation Dataset and Benchmark,
Online2007. Dataset, Segmentation. Dataset, BSDS. Code, Segmentation.
WWW Link. The updated code and data for the earlier paper.
See also Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics, A.

Martin, D.R.[David R.], Fowlkes, C.C.[Charless C.], Tal, D.[Doron], Malik, J.[Jitendra],
A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics,
ICCV01(II: 416-423).
Award, PAMI Helmholtz Prize, 2015.
A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms,
PercOrg01(xx-yy). Dataset, Human Segmentation. BSDS300 DAtaset Multiple human segmentations and a segmentation consistency measure. Human-human are consistent with the measure, different images are not consistent. Promised online availability. 1000 images with hand segmentations. Multiple hand segmentations.

Anke, B.[Bellmann], Olaf, H.[Hellwich], Volker, R.[Rodehorst], Ulas, Y.[Yilmaz],
A Benchmark Dataset for Performance Evaluation of Shape-from-X Algorithms,
ISPRS08(B3b: 67 ff).
PDF File.
Dataset, Shape from X.

Aksoy, Y.[Yagiz], Kim, C.[Changil], Kellnhofer, P.[Petr], Paris, S.[Sylvain], Elgharib, M.[Mohamed], Pollefeys, M.[Marc], Matusik, W.[Wojciech],
A Dataset of Flash and Ambient Illumination Pairs from the Crowd,
ECCV18(IX: 644-660).
Springer DOI
Dataset, Illumination.

Shi, B.X.[Bo-Xin], Mo, Z.P.[Zhi-Peng], Wu, Z.[Zhe], Duan, D.L.[Ding-Long], Yeung, S.K.[Sai-Kit], Tan, P.[Ping],
A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo,
PAMI(41), No. 2, February 2019, pp. 271-284.

Earlier: A1, A3, A2, A4, A5, A6: CVPR16(3707-3716)
Dataset, Photometric Stereo. Lighting, Taxonomy, Benchmark testing, Shape, Brain modeling, Cameras, Heuristic algorithms, Photometric stereo, benchmark, dataset, uncalibrated

Narasimhan, S.G.[Srinivasa G.], Wang, C.[Chi], Nayar, S.K.[Shree K.],
All the Images of an Outdoor Scene,
ECCV02(III: 148 ff.).
Springer DOI
PDF File.
Dataset, Outdoor Scene. A database of the same location every hour for 5 months. Registered and calibrated.
WWW Link. for the database.

Recurrent Asynchronous Multimodal Networks + Events, Frames, Semantic labels, and Depth maps recorded in CARLA simulator,
HTML Version. Code, Recurrent Networks. Code, Monocular Depth. Dataset, Monocular Depth.

Grosse, R.[Roger], Johnson, M.K.[Micah K.], Adelson, E.H.[Edward H.], Freeman, W.T.[William T.],
Ground truth dataset and baseline evaluations for intrinsic image algorithms,
Dataset, Shading. For shading and reflectance computations.

Scharstein, D.[Daniel], Szeliski, R.S.[Richard S.],
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms,
IJCV(47), No. 1-3, April-June 2002, pp. 7-42.
DOI Link
Code, Stereo. Dataset, Stereo. The data sets and code are also available:
WWW Link. Award, PAMI Everingham, 2015.

di Rita, M., Nascetti, A., Crespi, M.,
FOSS4G Date Assessment On the Isprs Optical Stereo Satellite Data: A Benchmark for DSM Generation,
DOI Link
Dataset, Stereo. benchmark dataset with several stereo data sets from space borne stereo sensors

Scharstein, D.[Daniel], Hirschmüller, H.[Heiko], Kitajima, Y.[York], Krathwohl, G.[Greg], Nešic, N.[Nera], Wang, X.[Xi], Westling, P.[Porter],
High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth,
Springer DOI
Dataset, Stereo.

Haeusler, R.[Ralf], Kondermann, D.[Daniel],
Synthesizing Real World Stereo Challenges,
Springer DOI
Dataset, Stereo.

Janoch, A.[Allison], Karayev, S.[Sergey], Jia, Y.Q.[Yang-Qing], Barron, J.T.[Jonathan T.], Fritz, M.[Mario], Saenko, K.[Kate], Darrell, T.J.[Trevor J.],
A category-level 3-D object dataset: Putting the Kinect to work,
Dataset, Stereo. Color and depth pairs.

Browatzki, B.[Bjorn], Fischer, J.[Jan], Graf, B.[Birgit], Bulthoff, H.H.[Heinrich H.], Wallraven, C.[Christian],
Going into depth: Evaluating 2D and 3D cues for object classification on a new, large-scale object dataset,
Dataset, Stereo.

Haeusler, R.[Ralf], Klette, R.[Reinhard],
Analysis of KITTI Data for Stereo Analysis with Stereo Confidence Measures,
UnOptFlow12(II: 158-167).
Springer DOI

Disparity Confidence Measures on Engineered and Outdoor Data,
Springer DOI

Benchmarking Stereo Data (Not the Matching Algorithms),
Springer DOI
Dataset, Stereo.

Janowski, A., Sawicki, P., Szulwic, J.,
Internet database for photogrammetric close range applications,
PDF File.
Dataset, Photogrammetry.

CVLab dense multi-view stereo image database,
HTML Version. Dataset, Stereo. Multiple views, ground level, of buildings

IS-3D: Data,
HTML Version. Dataset, Stereo. Multiple views of various structures.

Shao, S., Li, Z., Zhang, T., Peng, C., Yu, G., Zhang, X., Li, J., Sun, J.,
Objects365: A Large-Scale, High-Quality Dataset for Object Detection,
Dataset, Object Detection. feature extraction, image annotation, image classification, image segmentation, learning (artificial intelligence), Clocks

Wang, Q.[Qi], Zhu, G.K.[Guo-Kang], Yuan, Y.[Yuan],
Multi-spectral dataset and its application in saliency detection,
CVIU(117), No. 12, 2013, pp. 1748-1754.
Elsevier DOI
Dataset, Infrared. RGB+near infrared. Multi-spectral

Gauglitz, S.[Steffen], Höllerer, T.[Tobias], Turk, M.A.[Matthew A.],
Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking,
IJCV(94), No. 3, September 2011, pp. 335-360.
WWW Link.
WWW Link.
Dataset, Tracking. Present a dataset with ground truth for evaluation. And evaluation of camera tracking.

CUReT: Columbia-Utrecht Reflectance and Texture Database,
2006. Dataset, Texture.
WWW Link.

MIT Texture Data,
1995. Dataset, Texture.
HTML Version.

Texture Data,
2006. Dataset, Texture.
WWW Link.

Outex: New framework for empirical evaluation of texture analysis algorithms,
2006. Dataset, Texture.
WWW Link.

Texure Image Data,
2006. Dataset, Texture.
WWW Link. A variety of texture datasets. Includes Brodatz.

The KTH-TIPS and KTH-TIPS2 image databases,
2006. Dataset, Texture.
WWW Link. Textures under varying illumination, pose and scale. Extension of:
See also CUReT: Columbia-Utrecht Reflectance and Texture Database.

TILDA: Textile Texture Database,
1996. Dataset, Texture.
WWW Link.

Describable Textures Dataset (DTD),
2014 Dataset, Texture.
WWW Link.
See also Describing Textures in the Wild.

Hossain, S.[Shahera], Serikawa, S.[Seiichi],
Texture databases: A comprehensive survey,
PRL(34), No. 15, 2013, pp. 2007-2022.
Elsevier DOI
Dataset, Texture. Survey, Texture Datasets. Texture.

Xue, J.[Jia], Wadekar, P.[Paras], Zhang, H.[Hang], Teran, L.[Leizer], Dana, K.[Kristin], Nishino, K.[Ko],
Ground Terrain Database, GTOS,
HTML Version. Dataset, Texture.

Lee, S.K.[Seung-Kyu], Liu, Y.X.[Yan-Xi],
PSU Near-Regular Texture Database,
OnlinePSU, 2005.
WWW Link. Dataset, Texture.

Total found: 608

For more information on the topics, contact information, etc. see the annotated Computer Vision Bibliography or the Complete Conference Listing for Computer Vision and Image Analysis

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