Computer Vision Datasets

1,056 People Living Face & Anti-Spoofing Dataset – Multi-Scene, Multi-Expression. The collection scenes include indoor and outdoor scenes. The data includes male and female. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The data includes multiple postures, multiple expressions, and multiple anti-spoofing samples. The data can be used for tasks such as face payment, remote ID authentication, and face unlocking of mobile phone.

23,110 People Multi-race and Multi-pose Face Images Data. This data includes Asian race, Caucasian race, black race, brown race and Indians. Each subject were collected 29 images under different scenes and light conditions. The 29 images include 28 photos (multi light conditions, multiple poses and multiple scenes) + 1 ID photo. This data can be used for face recognition related tasks.

87,871 Images of 106 Facial Landmarks Annotation Data (complicated scenes)，this dataset includes yellow race, black race, white race and Indian people. In order to be more challenging, the data includes multiple scenes, multiple poses, different ages, light conditions and complicated expressions. This data can be used for tasks such as face detection and face recognition.

1,196 People Diverse Face Dataset – Multi-Race & Multi-Pose Images and Videos, This dataset contains face images and videos of 1,196 participants across multiple races and poses. Each person contributes 22 images and 40 videos. The collection environment includes indoor and outdoor scenes. This data can be used for face recognition and other tasks.

602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data,The data diversity includes headphones, body, background,and glasses.In terms of annotation, we adpoted segmentation annotations on headphones, body, background and glasses.The data can be used for tasks such as human body segmentation and the behavior detection of Video conference.

This dataset contains 874 videos of vandalism behaviors against public facilities recorded across indoor and outdoor environments. Each video documents individuals damaging, defacing, or destroying public property. The data covers multiple scenes, multiple shooting angles, and multiple resolutions. The data can be used for tasks such as human behavior detection, abnormal activity recognition, vandalism detection, and AI-powered surveillance tasks.

This dataset contains 1,274 videos capturing fence climbing behavior across indoor and outdoor environments. The data covers multiple scenes, multiple shooting angles, and multiple resolutions. The data can be used for tasks such ashuman behavior detection, abnormal activity recognition, trespassing detection, and other tasks.

This dataset contains 12,352 images capturing people handling or carrying objects in various real-world scenes, such as parks, warehouses, and streets. All pedestrians in each image are annotated, and the images are collected from a bird's-eye view. This data set can be used for human-object detection, object handling behavior recognition, crowd activity analysis, and AI surveillance model training.

This dataset contains 6,003 videos capturing crowd and gathering behaviors in various outdoor scenes. The data covers multiple scenes, multiple time periods, different density of the gathering crowd. The data can be used for tasks such as crowd behavior detection, gathering behavior recognition, crowd activity analysis, public safety monitoring and other tasks.