40 People – 3D&2D Living_Face & Anti

2D face recognition

3D face recognition

anti-spoofing

iPhone of multiple models

indoor scenes

outdoor scenes

multiple devices

multiple actions

multiple facial postures

multiple 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.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Data size

40 people, 48 videos and 150 groups (252 images) for each person

Population distribution

race distribution: Asian; gender distribution: 20 males, 20 females; age distribution: range from 18 to 57

Collecting environment

20 people in indoor scenes, 20 people in outdoor scenes

Data diversity

multiple devices, multiple actions, multiple facial postures, multiple anti-spoofing samples, multiple light conditions, multiple scenes

Device

cellphone, camera, iPhone of multiple models (iPhone X or more advanced iPhone models)

Data format

.mp4, .mov, .jpg, .xml, .json

Annotation content

label the person ID, race, gender, age, scene, facial action, light condition

Accuracy

based on the accuracy of the actions, the accuracy exceeds 97%; the accuracy of label annotation is not less than 97%

Recommended Dataset

5,993 People – Infrared Face Recognition Data

5,993 People – Infrared Face Recognition Data. The collecting scenes of this dataset include indoor scenes and outdoor scenes. The data includes male and female. The age distribution ranges from child to the elderly, the young people and the middle aged are the majorities. The collecting device is realsense D453i. The data diversity includes multiple age periods, multiple facial postures, multiple scenes. The data can be used for tasks such as infrared face recognition.

infrared face recognition indoor scenes outdoor scenes realsense D453i multiple age periods multiple facial postures multiple scenes

34,981 Images – Alpha Matte Human Body Segmentation Data (Fine Version)

34,981 Images – Alpha Matte Human Body Segmentation Data. The data includes indoor scenes and outdoor scenes. The dataset diversity includes multiple scenes, multiple age groups, multiple human body angles, multiple postures. In terms of annotation, alpha matte segmentation annotation was adopted for the human body. The data can be used for tasks such as alpha matte human body segmentation.

Alpha matte human body segmentation multiple scenes multiple age groups multiple human body angles multiple postures

4,458 People - 3D Facial Expressions Recognition Data

4,458 People - 3D Facial Expressions Recognition Data. The collection scenes include indoor scenes 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 different expressions, different ages, different races, different collecting scenes. This data can be used for tasks such as 3D facial expression recognition.

3D facial expressions recognition different expressions different ages different races different collecting scenes

5,199 People – 3D Face Recognition Images Data

5,199 People – 3D Face Recognition Images Data. The collection scene is indoor scene. 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 multiple facial postures, multiple light conditions, multiple indoor scenes. This data can be used for tasks such as 3D face recognition.

3D Face Recognition multiple facial postures multiple light conditions multiple indoor scenes

1,417 People – 3D Living_Face & Anti_Spoofing Data

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.

3D Living_Face & Anti_Spoofing various expressions facial postures anti-spoofing samples multiple light conditions multiple scenes

11,113 People - Face Recognition Data with Gauze Mask

11,113 People - Face Recognition Data with Gauze Mask, for each subject, 7 images were collected. The dataset diversity includes multiple mask types, multiple ages, multiple races, multiple light conditions and scenes.This data can be applied to computer vision tasks such as occluded face detection and recognition.

Face recognition Face occlusion Frontal face Gause mask

2,937 People with Occlusion and Multi-pose Face Recognition Data

2,937 People with Occlusion and Multi-pose Face Recognition Data, for each subject, 200 images were collected. The 200 images includes 4 kinds of light conditions * 10 kinds of occlusion cases (including non-occluded case) * 5 kinds of face pose. This data can be applied to computer vision tasks such as occluded face detection and recognition.rn

Face recognition Face occlusion Multi-pose per person Face with mask Multiple light conditions Multiplescenes blockage closure stoppage block stop obstruction blocking occluded front occlusive check closing embolism apoplexy shutdown hindrance blockade thrombosis impaction tampons arrest close congestion embolus fastener hitch obturation seal stopper abocclusion blocks clog clot clotting constipation holdup impediment occludent plug stoppages stopples stops tampon thrombus airlock barrier cap catch clogging cork plugging posture perplex puzzle mystify nonplus bewilder gravel flummox position baffle amaze dumbfound masquerade beat stick stupefy impersonate attitude place stance model present affectation mannerism attitudinize sit put submit show airs front propose suggest pretense propound affectedness raise strike a pose constitute facade personate show off advance pretend act bluff arrange put on airs peacock posing confront look meet front facing surface encounter side brave grimace experience visage address veneer countenance tackle cover oppose confronting defy expression aspect appearance cheek watch challenge nerve font overlook endure withstand suffer brass cope with dial head exterior typeface handle undergo be facing facade face up facial expression physiognomy beard boldness outside deal faces

4,082 Families-Family Face Data

4,082 Families-Family Face Data. The data includes various scenee, different families and 11 kinds of kinship pairs. One family photo was collected for each family, each family includes three family members at least. 11 kinds of kinship pairs, key points of two pupils, and bounding box of face were annotated. The data can be used for tasks such as kinship verification, searching for missing family members and organizing family photo albums.

family face 11 kinds of kinship pairs different families family image direct relative pairs key points of two pupils bounding box of face kinship verification searching for missing family members organizing family photo albums and genealogy research