{"id":"https://openalex.org/W2784318199","doi":"https://doi.org/10.1109/taffc.2018.2820048","title":"Segment-Based Methods for Facial Attribute Detection from Partial Faces","display_name":"Segment-Based Methods for Facial Attribute Detection from Partial Faces","publication_year":2018,"publication_date":"2018-03-27","ids":{"openalex":"https://openalex.org/W2784318199","doi":"https://doi.org/10.1109/taffc.2018.2820048","mag":"2784318199"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2018.2820048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2018.2820048","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1801.03546","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Upal Mahbub","orcid":"https://orcid.org/0000-0002-1861-8031"},"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":"Upal Mahbub","raw_affiliation_strings":["Center for Automation Research, UMIACS, University of Maryland, College Park, MD"],"raw_orcid":"https://orcid.org/0000-0002-1861-8031","affiliations":[{"raw_affiliation_string":"Center for Automation Research, UMIACS, University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sayantan Sarkar","orcid":"https://orcid.org/0000-0001-5213-0657"},"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":"Sayantan Sarkar","raw_affiliation_strings":["Center for Automation Research, UMIACS, University of Maryland, College Park, MD"],"raw_orcid":"https://orcid.org/0000-0001-5213-0657","affiliations":[{"raw_affiliation_string":"Center for Automation Research, UMIACS, University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":null,"display_name":"Rama Chellappa","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":"Rama Chellappa","raw_affiliation_strings":["Center for Automation Research, UMIACS, University of Maryland, College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Automation Research, UMIACS, University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.5784,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.8420639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":"4","first_page":"601","last_page":"613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.7756999731063843,"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":0.7756999731063843,"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/T10057","display_name":"Face and Expression Recognition","score":0.14800000190734863,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.04100000113248825,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.7493000030517578},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7364000082015991},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5490999817848206},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.4708000123500824},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.42410001158714294},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4032000005245209},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.39340001344680786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7753999829292297},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.7493000030517578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7480999827384949},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7364000082015991},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5490999817848206},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.4708000123500824},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43939998745918274},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.42410001158714294},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4032000005245209},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2978000044822693},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2736000120639801},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2619999945163727}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/taffc.2018.2820048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2018.2820048","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1801.03546","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.03546","pdf_url":"https://arxiv.org/pdf/1801.03546","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1801.03546","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.03546","pdf_url":"https://arxiv.org/pdf/1801.03546","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1530618081","https://openalex.org/W1834627138","https://openalex.org/W1965804146","https://openalex.org/W2009441118","https://openalex.org/W2061272711","https://openalex.org/W2102497689","https://openalex.org/W2126448884","https://openalex.org/W2295107390","https://openalex.org/W2324076412","https://openalex.org/W2471556897","https://openalex.org/W2488236012","https://openalex.org/W2536626143","https://openalex.org/W2548780814","https://openalex.org/W2551119324","https://openalex.org/W2585874438","https://openalex.org/W2605124728","https://openalex.org/W2963877604","https://openalex.org/W6620707391","https://openalex.org/W6631190155","https://openalex.org/W6638444622","https://openalex.org/W6679709651","https://openalex.org/W6694517276","https://openalex.org/W6736047048","https://openalex.org/W6739326283","https://openalex.org/W6742293275","https://openalex.org/W6743791556"],"related_works":[],"abstract_inverted_index":{"State-of-the-art":[0],"methods":[1,187],"of":[2,12,82,98,129,139,171],"attribute":[3,45,87,150,172],"detection":[4,46,173],"from":[5],"faces":[6],"almost":[7],"always":[8],"assume":[9],"the":[10,56,61,83,96,126,130,137,140,145,162,169],"presence":[11,138],"a":[13,33,65],"full,":[14],"unoccluded":[15],"face.":[16,142],"Hence,":[17],"their":[18],"performance":[19,170],"degrades":[20],"for":[21,102,152,189],"partially":[22,48],"visible":[23,127],"and":[24,55,105,147],"occluded":[25,49],"faces.":[26,50,177,191],"In":[27],"this":[28],"paper,":[29],"we":[30,166],"introduce":[31],"SPLITFACE,":[32],"deep":[34],"convolutional":[35],"neural":[36],"network-based":[37],"method":[38,63],"that":[39,165,181],"is":[40],"explicitly":[41],"designed":[42],"to":[43,69,88,108,113,134,160],"perform":[44],"in":[47,75,125],"Taking":[51],"several":[52],"facial":[53,77,149],"segments":[54],"full":[57],"face":[58],"as":[59],"input,":[60],"proposed":[62],"takes":[64],"data":[66],"driven":[67],"approach":[68],"determine":[70],"which":[71,76,94,122],"attributes":[72,121],"are":[73,123],"localized":[74,124],"segments.":[78],"The":[79],"unique":[80],"architecture":[81],"network":[84],"allows":[85],"each":[86],"be":[89],"predicted":[90],"by":[91],"multiple":[92],"segments,":[93],"permits":[95],"implementation":[97],"committee":[99],"machine":[100],"techniques":[101],"combining":[103],"local":[104],"global":[106],"decisions":[107],"boost":[109],"performance.":[110],"With":[111],"access":[112],"segment-based":[114],"predictions,":[115],"SPLITFACE":[116,182],"can":[117,167],"predict":[118],"well":[119],"those":[120],"parts":[128],"face,":[131],"without":[132],"having":[133],"rely":[135],"on":[136,175],"whole":[141],"We":[143,155],"use":[144],"CelebA":[146],"LFWA":[148],"datasets":[151],"standard":[153],"evaluations.":[154],"also":[156],"modify":[157],"both":[158],"datasets,":[159],"occlude":[161],"faces,":[163],"so":[164],"evaluate":[168],"algorithms":[174],"partial":[176,190],"Our":[178],"evaluation":[179],"shows":[180],"significantly":[183],"outperforms":[184],"other":[185],"recent":[186],"especially":[188]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2018-01-26T00:00:00"}
