{"id":"https://openalex.org/W2554757535","doi":"https://doi.org/10.1109/btas.2017.8272731","title":"UMDFaces: An annotated face dataset for training deep networks","display_name":"UMDFaces: An annotated face dataset for training deep networks","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2554757535","doi":"https://doi.org/10.1109/btas.2017.8272731","mag":"2554757535"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2017.8272731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1611.01484","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023195442","display_name":"Ankan Bansal","orcid":"https://orcid.org/0000-0001-5578-4277"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ankan Bansal","raw_affiliation_strings":["University of Maryland, College Park","University of Maryland - College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083725203","display_name":"Anirudh Nanduri","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anirudh Nanduri","raw_affiliation_strings":["University of Maryland, College Park","University of Maryland - College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101861410","display_name":"Carlos D. Castillo","orcid":"https://orcid.org/0000-0001-5308-4824"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carlos D. Castillo","raw_affiliation_strings":["University of Maryland, College Park","University of Maryland - College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101768429","display_name":"Rajeev Ranjan","orcid":"https://orcid.org/0000-0003-2553-823X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajeev Ranjan","raw_affiliation_strings":["University of Maryland, College Park","University of Maryland - College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102762707","display_name":"Rama Chellappa","orcid":"https://orcid.org/0000-0002-7638-1650"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rama Chellappa","raw_affiliation_strings":["University of Maryland, College Park","University of Maryland - College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5023195442"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.7795431,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.87606234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"464","last_page":"473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9782000184059143,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8351061344146729},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7676922082901001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6778389811515808},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6652054190635681},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6606118679046631},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.585791826248169},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5535547733306885},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.45791521668434143},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.44486385583877563},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44470325112342834},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3894515037536621}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8351061344146729},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7676922082901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6778389811515808},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6652054190635681},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6606118679046631},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.585791826248169},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5535547733306885},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.45791521668434143},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44486385583877563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44470325112342834},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3894515037536621},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/btas.2017.8272731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1611.01484","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.01484","pdf_url":"https://arxiv.org/pdf/1611.01484","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2554757535","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1611.01484","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1611.01484","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1611.01484","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1611.01484","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.01484","pdf_url":"https://arxiv.org/pdf/1611.01484","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Gender equality","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2554757535.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1834627138","https://openalex.org/W1921147789","https://openalex.org/W1949778830","https://openalex.org/W1950843348","https://openalex.org/W1990937109","https://openalex.org/W2012885984","https://openalex.org/W2019464758","https://openalex.org/W2024922353","https://openalex.org/W2096733369","https://openalex.org/W2111372597","https://openalex.org/W2115579991","https://openalex.org/W2117539524","https://openalex.org/W2129305389","https://openalex.org/W2157285372","https://openalex.org/W2304348237","https://openalex.org/W2339268922","https://openalex.org/W2474608001","https://openalex.org/W2727093475","https://openalex.org/W2963671154","https://openalex.org/W2963721882","https://openalex.org/W2964014798","https://openalex.org/W6607458078","https://openalex.org/W6639102338","https://openalex.org/W6649863312","https://openalex.org/W6662335928","https://openalex.org/W6681239517","https://openalex.org/W6681342084","https://openalex.org/W6684191040","https://openalex.org/W6700903540","https://openalex.org/W6726453277"],"related_works":["https://openalex.org/W1834627138","https://openalex.org/W1509966554","https://openalex.org/W3207264592","https://openalex.org/W2620308114","https://openalex.org/W2023161323","https://openalex.org/W2963566548","https://openalex.org/W2325939864","https://openalex.org/W2515770085","https://openalex.org/W2981436931","https://openalex.org/W3171728179","https://openalex.org/W3110818700","https://openalex.org/W3199596647","https://openalex.org/W3138908442","https://openalex.org/W3038771692","https://openalex.org/W2967444841","https://openalex.org/W3206136719","https://openalex.org/W2397085567","https://openalex.org/W2962902099","https://openalex.org/W3010372886","https://openalex.org/W2905236541"],"abstract_inverted_index":{"Recent":[0],"progress":[1],"in":[2,90],"face":[3,63,80,168],"detection":[4],"(including":[5],"keypoint":[6,145],"detection),":[7],"and":[8,21,36,48,102,107,125,131],"recognition":[9,81],"is":[10],"mainly":[11],"being":[12],"driven":[13],"by":[14,33,135,150],"(i)":[15],"deeper":[16],"convolutional":[17],"neural":[18,138],"network":[19],"architectures,":[20],"(ii)":[22],"larger":[23,47],"datasets.":[24],"However,":[25],"most":[26],"of":[27,72,128,144,161],"the":[28,88,142,159,162],"large":[29,97],"datasets":[30,51,169],"are":[31,37],"maintained":[32],"private":[34],"companies":[35],"not":[38],"publicly":[39,166],"available.":[40],"The":[41],"academic":[42],"computer":[43],"vision":[44],"community":[45],"needs":[46],"more":[49],"varied":[50],"to":[52],"make":[53],"further":[54],"progress.":[55],"In":[56,140],"this":[57,91],"paper":[58],"we":[59,157],"introduce":[60,77],"a":[61,78,96,136],"new":[62,79],"dataset,":[64],"called":[65],"UMDFaces,":[66],"which":[67,84],"has":[68,147],"367,888":[69],"annotated":[70,103],"faces":[71],"8,277":[73],"subjects.":[74],"We":[75,93,110,118],"also":[76,119],"evaluation":[82],"protocol":[83],"will":[85],"help":[86],"advance":[87],"state-of-the-art":[89],"area.":[92],"discuss":[94],"how":[95],"dataset":[98,163],"can":[99],"be":[100],"collected":[101],"using":[104],"human":[105,112],"annotators":[106],"deep":[108],"networks.":[109],"provide":[111,120],"curated":[113],"bounding":[114],"boxes":[115],"for":[116,152],"faces.":[117],"estimated":[121],"pose":[122],"(roll,":[123],"pitch":[124],"yaw),":[126],"locations":[127],"twenty-one":[129],"key-points":[130],"gender":[132],"information":[133],"generated":[134],"pre-trained":[137],"network.":[139],"addition,":[141],"quality":[143,160],"annotations":[146],"been":[148],"verified":[149],"humans":[151],"about":[153],"115,000":[154],"images.":[155],"Finally,":[156],"compare":[158],"with":[164],"other":[165],"available":[167],"at":[170],"similar":[171],"scales.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}