WallFlower dataset: 用于评价背景建模算法的好坏. Ground-truth foreground provided.
Foreground/Background segmentation and Stereo dataset: from Microsoft Cambridge.
VISOR: Video Surveillance Online Repositiory: 大量的视频和路面实况.
3D Photography Dataset
Multi-model, multi-camera meeting room dataset
Advanced Video and Signal based Surveillance: 各种用于跟踪和检测的数据集.
Caltech image collections: 用于目标物体检测，分割和分类
INRIA Datasets: 车辆, 人, 马, 人类行为等
CAVIAR surveillance Dataset
Videos for Head Tracking
Pedestrian dataset from MIT
Shadow detection datasets
Flash and non-Flash dataset
Experiments on skin region detection and tracking: 包括一个ground-truthed dataset
MIT Face Dataset
MIT Car Datasets
MIT Street Scenes: CBCL StreetScenes Challenge Framework 是一个图像、注释、软件和性能检测的对象集[cars, pedestrians, bicycles, buildings, trees, skies, roads, sidewalks, and stores]
LabelMe Dataset: 超过150,000已经标注的照片.
MuHAVi: Multicamera Human Action Video DataA large body of human action video data using 8 cameras. Includes manually annotated silhouette data. 用于测试人行为的数据集
INRIA Xmas Motion Acquisition Sequences (IXMAS): Multiview dataset for view-invariant human action recognition.
i-LIDS datasets: UK Government benchmark datasets for automated surveillance.
The Daimler Pedestrian Detection Benchmark: contains 15,560 pedestrian and non-pedestrian samples (image cut-outs) and 6744 additional full images not containing pedestrians for bootstrapping. The test set contains more than 21,790 images with 56,492 pedestrian labels (fully visible or partially occluded), captured from a vehicle in urban traffic.
Stereo Pedestrian Detection Evaluation Dataset: a dataset for evaluating pedestrian detection using stereo camera images and video. 用于测试行人检测算法的数据集
Colour video and Thermal infrared datasets: Dataset of videos in colour and thermal infrared. Videos are aligned temporally and spatially. Ground-truth for object tracking is provided.
http://hi.baidu.com/56908268/blog/item/4f9fc51b4e662ff6af51338a.html
Datasets
- MIT CSAIL LabelMe, open annotation tool related tech report
- PASCAL Visual Object Classes challenges (2005-2007)
- Wordnet
- Caltech101
- Caltech256
- TREC Video Retrieval Evaluation
- Oxford buildings dataset
- Photo-tourism patches
- UIUC Car detection dataset
- CMU Face databases
- Animals on the Web data
- ETH-80
- Graz 02
- MIT Objects and Scenes
- NYU NORB dataset
- Columbia COIL
- Oxford flowers dataset
- SFU activity dataset (sports)
- Princeton events dataset
- Weizmann activity videos
- Data collections of detected faces, from Oxford VGG
- Face data from Buffy episode, from Oxford VGG
- University of Cambridge face data from films [go to Data link]
- Reuters
- Dataset list from the Computer Vision Homepage
- Image Parsing
- Various other datasets from the Oxford Visual Geometry group
- INRIA Holiday images dataset
- Movie human actions dataset from Laptev et al.
- ESP game dataset
- Bastian Leibe’s dataset page: pedestrians, vehicles, cows, etc.
- UMass Labeled Faces in the Wild
- FaceTracer database from Columbia
WallFlower dataset: For evaluating background modelling algorithms. Ground-truth foreground provided.
Foreground/Background segmentation and Stereo dataset: from Microsoft Cambridge.
VISOR: Video Surveillance Online Repositiory: Lots of videos and ground truth.
3D Photography Dataset
Multi-model, multi-camera meeting room dataset
Advanced Video and Signal based Surveillance: a variety datasets for tracking and detection.
Caltech image collections: object detection, segmentation and classification
INRIA Datasets: Cars, people, horses, human actions, etc.
CAVIAR surveillance Dataset
Videos for Head Tracking
Pedestrian dataset from MIT
Shadow detection datasets
Flash and non-Flash dataset
Experiments on skin region detection and tracking: it includes a ground-truthed dataset
MIT Face Dataset
MIT Car Datasets
MIT Street Scenes: CBCL StreetScenes Challenge Framework is a collection of images, annotations, software and performance measures for object detection [cars, pedestrians, bicycles, buildings, trees, skies, roads, sidewalks, and stores]
LabelMe Dataset: Over 150,000 images with objects annotated and labelled.
MuHAVi: Multicamera Human Action Video DataA large body of human action video data using 8 cameras. Includes manually annotated silhouette data.
INRIA Xmas Motion Acquisition Sequences (IXMAS): Multiview dataset for view-invariant human action recognition.
i-LIDS datasets: UK Government benchmark datasets for automated surveillance.
The Daimler Pedestrian Detection Benchmark: contains 15,560 pedestrian and non-pedestrian samples (image cut-outs) and 6744 additional full images not containing pedestrians for bootstrapping. The test set contains more than 21,790 images with 56,492 pedestrian labels (fully visible or partially occluded), captured from a vehicle in urban traffic.
Stereo Pedestrian Detection Evaluation Dataset: a dataset for evaluating pedestrian detection using stereo camera images and video.
Colour video and Thermal infrared datasets: Dataset of videos in colour and thermal infrared. Videos are aligned temporally and spatially. Ground-truth for object tracking is provided.
Dataset lists
List of Databases: Includes multiple face datasets, texture datasets, etc.
UIUC Datasets: Includes... Fifteen Scene Categories, 3D Object Recognition Stereo Dataset, 3D Photography Dataset, Visual Datasets, Birds, Butterflies, Object Recognition Database, Texture Database and Video Sequences.
OTCBVS Datasets: Several datasets that include non-visual data, such as thermal infrared and NIR.
List of "emotional" databases: