[{"@type":"PropertyValue","name":"Data size","value":"10,543 people, 4 images per person"},{"@type":"PropertyValue","name":"Race distribution","value":"Asian"},{"@type":"PropertyValue","name":"Gender distribution","value":"5,030 males and 5,513 females"},{"@type":"PropertyValue","name":"Age distribution","value":"ranging from teenager to the elderly, the middle-aged and young people are the majorities"},{"@type":"PropertyValue","name":"Collecting environment","value":"including indoor and outdoor scenes"},{"@type":"PropertyValue","name":"Data diversity","value":"different shooting heights, different ages, different light conditions and scenes"},{"@type":"PropertyValue","name":"Device","value":"cellphone"},{"@type":"PropertyValue","name":"Data format","value":".jpg"}]
{"id":1101,"datatype":"1","titleimg":"https://res.datatang.com/asset/productNew/APY211231001.png?Expires=2007353703&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=W9IYD0z/VIDD2yXz6MP9SXOqLhs%3D","type1":"147","type1str":null,"type2":"147","type2str":null,"dataname":"10,543 People - Face Recognition Data at Ticket Gate","datazy":[{"title":"Data size","value":"10,543 people, 4 images per person"},{"title":"Race distribution","value":"Asian"},{"title":"Gender distribution","value":"5,030 males and 5,513 females"},{"title":"Age distribution","value":"ranging from teenager to the elderly, the middle-aged and young people are the majorities"},{"title":"Collecting environment","value":"including indoor and outdoor scenes"},{"title":"Data diversity","value":"different shooting heights, different ages, different light conditions and scenes"},{"title":"Device","value":"cellphone"},{"title":"Data format","value":".jpg"}],"datatag":"Different shooting heights,Different ages,Different light conditions and scenes","technologydoc":null,"downurl":null,"datainfo":"","standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":"","samplePresentation":["mp4",""],"officialSummary":"10,543 People - Face Recognition Data at Ticket Gate, for each subject, 4 images were collected. The dataset diversity includes different shooting heights, different ages, different light conditions and scenes.This data can be applied to computer vision tasks such as face detection and recognition.","dataexampl":"","datakeyword":["Different shooting heights","Different ages","Different light conditions and scenes"],"isDelete":null,"ids":null,"idsList":null,"datasetCode":null,"productStatus":null,"tagTypeEn":"Task Type,Modalities","tagTypeZh":null,"website":null,"samplePresentationList":null,"datazyList":null,"keyInformationList":null,"dataexamplList":null,"bgimg":null,"datazyScriptList":null,"datakeywordListString":null,"sourceShowPage":"computer","BGimg":"","voiceBg":["/shujutang/static/image/comm/audio_bg.webp","/shujutang/static/image/comm/audio_bg2.webp","/shujutang/static/image/comm/audio_bg3.webp","/shujutang/static/image/comm/audio_bg4.webp","/shujutang/static/image/comm/audio_bg5.webp"],"single":"yes"}
10,543 People - Face Recognition Data at Ticket Gate
Different shooting heights
Different ages
Different light conditions and scenes
10,543 People - Face Recognition Data at Ticket Gate, for each subject, 4 images were collected. The dataset diversity includes different shooting heights, different ages, different light conditions and scenes.This data can be applied to computer vision tasks such as face detection and recognition.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data size
10,543 people, 4 images per person
Race distribution
Asian
Gender distribution
5,030 males and 5,513 females
Age distribution
ranging from teenager to the elderly, the middle-aged and young people are the majorities
Collecting environment
including indoor and outdoor scenes
Data diversity
different shooting heights, different ages, different light conditions and scenes
Device
cellphone
Data format
.jpg
Sample
Waiting For Data
Recommended Dataset
10 People - 3D&2D Living_Face & Anti_Spoofing Data
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.
5,172 People - Multi-race Juvenile and Multi-pose Facial Images
5,172 People - Multi-race Juvenile and Multi-pose Facial Images. This data includes black people, Caucasian people and brown people. Each subject was collected 10 images. (The 10 images include 10 photos in different lighting, different face poses and different collection environments). This data can be used for face recognition related tasks.
Different face poses and racesDifferent agesDifferent lightingDifferent collection environments
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
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
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 recognitionFace occlusionFrontal faceGause 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 occlusionMulti-pose per personFace with maskMultiple light conditions Multiplescenesblockageclosurestoppageblockstopobstructionblockingoccludedfrontocclusivecheckclosingembolismapoplexyshutdownhindranceblockadethrombosisimpactiontamponsarrestclosecongestionembolusfastenerhitchobturationsealstopperabocclusionblocksclogclotclottingconstipationholdupimpedimentoccludentplugstoppagesstopplesstopstamponthrombusairlockbarriercapcatchcloggingcorkpluggingpostureperplexpuzzlemystifynonplusbewildergravelflummoxpositionbaffleamazedumbfoundmasqueradebeatstickstupefyimpersonateattitudeplacestancemodelpresentaffectationmannerismattitudinizesitputsubmitshowairsfrontproposesuggestpretensepropoundaffectednessraisestrikeaposeconstitutefacadepersonateshowoffadvancepretendactbluffarrangeputonairspeacockposingconfrontlookmeetfrontfacingsurfaceencountersidebravegrimaceexperiencevisageaddressveneercountenancetacklecoveropposeconfrontingdefyexpressionaspectappearancecheekwatchchallengenervefontoverlookendurewithstandsufferbrasscopewithdialheadexteriortypefacehandleundergobefacingfacadefaceupfacialexpressionphysiognomybeardboldnessoutsidedealfaces
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