Computer Vision Datasets

1,056 People Living_face & Anti-Spoofing Data. 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.

1,196 People Multi-race and Multi-pose Face Images & Videos Data, 22 images and 40 videos per person. The collection environment includes indoor and outdoor scenes. This data can be used for face recognition and other tasks.

100 People - Face Detection & Face 96 Landmarks Annotation Data. The data includes multiple ages, multiple time periods and multiple races (Caucasian, Black, Indian). The driver behaviors includes dangerous behavior, fatigue behavior and visual movement behavior. In terms of device, infrared cameras were applied. In terms of annotation, each individual consists of 274 to 299 photos, with annotations for detected facial bounding boxes and 96 facial landmarks. The data can be used for tasks such as facial detection, 96 facial landmark recognition.

The 110 People – Human Face Image Data is gathered through camera shot involving 110 native speakers, developed with a proper balance of gender ratio and age group distribution covering major colour tones human race. 2100 pictures per person with glasses, expressions, camera shooting angle, and lighting conditions. All Attributes are annotated, including gender, age, expression, etc. The overall accuracy rate is ≥ 97%.

568 People - Face Detection & Face 106 Landmarks & Human Body Segmentation Annotation Data in Online Conference Scenes. The ethnic groups include East Asians, Caucasians, Blacks, and Browns, with a primary focus on young adults. Various indoor office scenes were captured, including meeting rooms, cafes, libraries, and bedrooms. In terms of annotation, each individual consists of 61 to 64 photos, with annotations for detected facial bounding boxes and 106 facial landmarks, as well as segmentation annotations for the human body. The data can be used for tasks such as facial detection, 106 facial landmark recognition, and human body segmentation.

1,417 People – 3D Living_Face & Anti_Spoofing Data. The collection scenes include indoor and outdoor scenes. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iPhone XR. The data diversity includes various expressions, facial postures, anti-spoofing samples, multiple light conditions, multiple scenes. This data can be used for tasks such as 3D face recognition, 3D Living_Face & Anti_Spoofing.

200 Vietnamese– 3D Living_Face & Anti_Spoofing Data. The collection scenes include indoor and outdoor scenes. The dataset includes males and females. The age distribution includes under 18 years old, 18 to 45 years old, 46 to 60 years old, over 60 years old. The device includes iPhone X, iPhone XR, iPhone11, iPhone12, iPhone13. The data diversity includes various expressions, facial postures, anti-spoofing samples, multiple light conditions, multiple scenes. This data can be used for tasks such as 3D face recognition, 3D Living_Face & Anti_Spoofing.

4,484 people multi-race – infrared face recognition data. The collecting scenes of this dataset include indoor scenes and outdoor scenes. The data includes male and female. The race distribution includes Asian, Black, Caucasian and Brown people. The age distribution ranges from child to the elderly, the young people and the middle aged are the majorities. The collecting device is DV-DH4,044S305AD. The data diversity includes multiple age periods, multiple facial postures, multiple scenes. The data can be used for tasks such as infrared face recognition. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.