[{"@type":"PropertyValue","name":"Data size","value":"70 people, 48 videos and 150 groups (252 images) for each person"},{"@type":"PropertyValue","name":"Race distribution","value":"Asian, Black race, Caucasian"},{"@type":"PropertyValue","name":"Gender distribution","value":"males, females"},{"@type":"PropertyValue","name":"Age distribution","value":"range from 18 to 50"},{"@type":"PropertyValue","name":"Collecting environment","value":"indoor scenes, outdoor scenes"},{"@type":"PropertyValue","name":"Data diversity","value":"multiple devices, multiple actions, multiple facial postures, multiple anti-spoofing samples, multiple light conditions, multiple scenes"},{"@type":"PropertyValue","name":"Device","value":"cellphone, camera, iPhone of multiple models (iPhone X or more advanced iPhone models)"},{"@type":"PropertyValue","name":"Data format","value":".mp4, .mov, .jpg, .xml, .json"},{"@type":"PropertyValue","name":"Annotation content","value":"label the person ID, race, gender, age, scene, facial action, light condition"},{"@type":"PropertyValue","name":"Accuracy rate","value":"Collection accuracy: based on the accuracy of the actions, the accuracy exceeds 97% Annotation accuracy: the accuracy of label annotation is not less than 97%"}]
{"id":1991,"datatype":"1","titleimg":"https://www.nexdata.ai/shujutang/static/image/index/datatang_tuxiang_default.webp","type1":"147","type1str":null,"type2":"149","type2str":null,"dataname":"70 Person Multi-race 3D&2D Living_Face & Anti_Spoofing Data","datazy":[{"title":"Data size","content":"70 people, 48 videos and 150 groups (252 images) for each person"},{"title":"Race distribution","content":"Asian, Black race, Caucasian"},{"title":"Gender distribution","content":"males, females"},{"title":"Age distribution","content":"range from 18 to 50"},{"title":"Collecting environment","content":"indoor scenes, outdoor scenes"},{"title":"Data diversity","content":"multiple devices, multiple actions, multiple facial postures, multiple anti-spoofing samples, multiple light conditions, multiple scenes"},{"title":"Device","content":"cellphone, camera, iPhone of multiple models (iPhone X or more advanced iPhone models)"},{"title":"Data format","content":".mp4, .mov, .jpg, .xml, .json"},{"title":"Annotation content","content":"label the person ID, race, gender, age, scene, facial action, light condition"},{"title":"Accuracy rate","content":"Collection accuracy: based on the accuracy of the actions, the accuracy exceeds 97% Annotation accuracy: the accuracy of label annotation is not less than 97%"}],"datatag":"Living_Face & Anti_Spoofing,Multi-race,3D mask,Anti-spoofing","technologydoc":null,"downurl":null,"datainfo":null,"standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":null,"samplePresentation":[],"officialSummary":"70 People Multi-race 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 18-50 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.","dataexampl":null,"datakeyword":["Living_Face & Anti_Spoofing","Multi-race","3D mask","Anti-spoofing"],"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","dataShowType":"[{\"code\":\"0\",\"language\":\"ZH\"},{\"code\":\"1\",\"language\":\"ZH\"},{\"code\":\"2\",\"language\":\"EN\"},{\"code\":\"3\",\"language\":\"EN\"}]","productNameEn":"70 Person Multi-race 3D&2D Living_Face & Anti_Spoofing Data","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"]}
70 Person Multi-race 3D&2D Living_Face & Anti_Spoofing Data
Living_Face & Anti_Spoofing
Multi-race
3D mask
Anti-spoofing
70 People Multi-race 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 18-50 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
70 people, 48 videos and 150 groups (252 images) for each person
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 rate
Collection accuracy: based on the accuracy of the actions, the accuracy exceeds 97% Annotation accuracy: the accuracy of label annotation is not less than 97%
Specifications
Sample
Recommended Dataset
