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.

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.

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.

10 People - 3D&2D Living_Face & Anti_Spoofing Data. The collection scenes is indoor 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.

40 People – 3D&2D Living_Face & Anti_Spoofing Data. The collection scenes are indoor scenes and outdoor scenes. The dataset includes males and females, the age distribution is 18-57 years old. The device includes cellphone, camera, iPhone of multiple models (iPhone X or more advanced iPhone models). The data diversity includes multiple devices, multiple actions, multiple facial postures, multiple anti-spoofing samples, multiple light conditions, multiple scenes. This data can be used for tasks such as 2D Living_Face & Anti_Spoofing, 2D face recognition, 3D face recognition, 3D Living_Face & Anti_Spoofing.

208 Vietnamese– 2D 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 race distribution is Vietnamese. The data includes various expressions, postures, anti-spoofing samples, multiple light conditions, multiple scenes. The data can be used for tasks such as face payment, remote ID authentication, and face unlocking of mobile phone.

5,957 Images – Fine Semantic Segmentation Data of Scenes. The scene of this dataset is outdoor scenes. The data diversity includes multiple scenes, different time periods. For annotation, segmentation annotation was adopted for the sky region in the images. The data can be used for fine semantic segmentation and other tasks.

49,945 Images Human Costume & Apparel Accessory Segmentation Data. The gender distribution includes female and male, the race distribution is Asian, Caucasian and black race, the age distribution is teenager, young and middle-aged. The data diversity includes multiple scenes, multiple light conditions, multiple types of costume (upper garment, lower garment, and shoes), and multiple apparel accessories (bag, glasses, accessories, etc.). In terms of annotation, semantic segmentation of 47 categories object (including background, costume and apparel accessory) was adopted. The dataset can be used for tasks such as human costume & apparel accessory segmentation and fashion recommendation.