Links to free data sets for computer vision applications. If you would like to submit a link, please contact us.

LFW: Labeled Faces in the Wild

Labeled Faces in the Wild is a data set of face photographs designed for studying the problem of unconstrained face recognition.


Managing photo collections involves a variety of image quality assessment tasks, e.g. the selection of the "best" photos. Detecting near-duplicates is a prerequisite for automating these tasks.

Extreme View Dataset

This dataset is a two-view matching evaluation dataset with extreme viewpoint changes.

UvA Person Tracking Benchmarks

Various benchmarks related to 3D (single, multiple) person tracking and pose recovery from overlapping monocular cameras. In- and outdoor.

Daimler Pedestrian Benchmarks

Various benchmarks related to pedestrian detection, classification, segmentation and path prediction. Pedestrian data as observed from on-board a vehicle in traffic. Mono, stereo and multi-cue.

Caltech Pedestrian Detection Benchmark

The Caltech Pedestrian Dataset consists of approximately 10 hours of 640x480 30Hz video taken from a vehicle driving through regular traffic in an urban environment.

Berkeley Multimodal Human Action Database (MHAD)

The Berkeley Multimodal Human Action Database (MHAD) contains 11 actions performed by 7 male and 5 female subjects in the range 23-30 years of age except for one elderly subject.

ALOT: Amsterdam Library Of Textures

ALOT is a color image collection of 250 rough textures, recorded for scientific purposes.

JPL First-Person Interaction dataset

JPL First-Person Interaction dataset (JPL-Interaction dataset) is composed of human activity videos taken from a first-person viewpoint.

50 Salads

Activity recognition research has shifted focus from distinguishing full-body motion patterns to recognizing complex interactions of multiple entities.


YouCook is an Annotated Data Set of Unconstrained Third-Person Cooking Videos and is prepared from 88 open-source YouTube cooking videos.

Change Detection Database

Change Detection database encapsulates a rigorous and comprehensive academic benchmarking effort for testing and ranking existing and new algorithms for change and motion detection much like the Mi