{"id":"https://openalex.org/W3161557735","doi":"https://doi.org/10.1109/icpr48806.2021.9413133","title":"Face Image Quality Assessment for Model and Human Perception","display_name":"Face Image Quality Assessment for Model and Human Perception","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161557735","doi":"https://doi.org/10.1109/icpr48806.2021.9413133","mag":"3161557735"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9413133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100420347","display_name":"Ken Chen","orcid":"https://orcid.org/0000-0003-4013-5279"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ken Chen","raw_affiliation_strings":["Shanghai SenseTime Intelligent Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai SenseTime Intelligent Technology Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059321688","display_name":"Yichao Wu","orcid":"https://orcid.org/0000-0003-4496-9959"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yichao Wu","raw_affiliation_strings":["Shanghai SenseTime Intelligent Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai SenseTime Intelligent Technology Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059454654","display_name":"Zhenmao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhenmao Li","raw_affiliation_strings":["Shanghai SenseTime Intelligent Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai SenseTime Intelligent Technology Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102540250","display_name":"Yudong Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yudong Wu","raw_affiliation_strings":["Shanghai SenseTime Intelligent Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai SenseTime Intelligent Technology Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100751872","display_name":"Ding Liang","orcid":"https://orcid.org/0000-0001-9774-4687"},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ding Liang","raw_affiliation_strings":["Shanghai SenseTime Intelligent Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai SenseTime Intelligent Technology Co., Ltd","institution_ids":["https://openalex.org/I4210153682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210153682"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"3003","last_page":"3010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9969000220298767,"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":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7468767166137695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6433419585227966},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.6271877884864807},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6064023971557617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5876891613006592},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5718382596969604},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.49028900265693665},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.45766547322273254},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4559628665447235},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.44329890608787537},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.41800910234451294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37250810861587524},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2990250587463379},{"id":"https://openalex.org/keywords/evaluation-methods","display_name":"Evaluation methods","score":0.17249733209609985},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.09983822703361511},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08978518843650818},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07845282554626465}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7468767166137695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6433419585227966},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.6271877884864807},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6064023971557617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5876891613006592},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5718382596969604},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.49028900265693665},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.45766547322273254},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4559628665447235},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.44329890608787537},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41800910234451294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37250810861587524},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2990250587463379},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.17249733209609985},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.09983822703361511},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08978518843650818},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07845282554626465},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"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/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9413133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1526662621","https://openalex.org/W1563941117","https://openalex.org/W1979115138","https://openalex.org/W1991777678","https://openalex.org/W1997011019","https://openalex.org/W1998808035","https://openalex.org/W2000130062","https://openalex.org/W2051596736","https://openalex.org/W2096733369","https://openalex.org/W2133665775","https://openalex.org/W2144172034","https://openalex.org/W2145287260","https://openalex.org/W2163870506","https://openalex.org/W2170947705","https://openalex.org/W2194775991","https://openalex.org/W2515770085","https://openalex.org/W2620498498","https://openalex.org/W2793964976","https://openalex.org/W2900061109","https://openalex.org/W2910603373","https://openalex.org/W2919115771","https://openalex.org/W2945433212","https://openalex.org/W2962737770","https://openalex.org/W2962898354","https://openalex.org/W2963163009","https://openalex.org/W2963216120","https://openalex.org/W2963446712","https://openalex.org/W2963671154","https://openalex.org/W2963839617","https://openalex.org/W2969985801","https://openalex.org/W2970971581","https://openalex.org/W2975127015","https://openalex.org/W3006276840","https://openalex.org/W3099206234","https://openalex.org/W4289294802","https://openalex.org/W4295312788","https://openalex.org/W6631483996","https://openalex.org/W6681239517","https://openalex.org/W6685134578","https://openalex.org/W6739001957","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W2364252372","https://openalex.org/W2466958844","https://openalex.org/W3035701170","https://openalex.org/W1552490587","https://openalex.org/W2804751933","https://openalex.org/W2245293081","https://openalex.org/W1973829424","https://openalex.org/W3209787365","https://openalex.org/W4311304958","https://openalex.org/W4287019296"],"abstract_inverted_index":{"Practical":[0],"face":[1],"image":[2],"quality":[3,25,65,79,145],"assessment":[4],"(FIQA)":[5],"models":[6,38,49,119],"are":[7,27,58],"trained":[8,41],"under":[9],"the":[10,35,47,55,83,109,122,133,152,168,184],"supervision":[11],"of":[12,100,124,186,190],"labeled":[13,24,170],"data,":[14],"which":[15,61],"requires":[16],"more":[17],"or":[18],"less":[19],"human":[20,23,169],"labor.":[21],"The":[22],"scores":[26,57,66,80],"consistent":[28],"with":[29,42,50],"perceptual":[30],"intuition":[31],"but":[32],"laborious.":[33],"On":[34],"other":[36],"hand,":[37],"can":[39],"be":[40],"data":[43,125],"generated":[44],"automatically":[45],"by":[46,120,155],"recognition":[48,56,156],"artificially":[51],"selected":[52],"references.":[53],"However,":[54],"sometimes":[59],"inaccurate,":[60],"may":[62],"give":[63],"wrong":[64,153],"during":[67],"FIQA":[68,118],"training.":[69],"In":[70,129],"this":[71],"paper,":[72],"we":[73,86,111,140],"propose":[74,112],"a":[75,113,142],"labour-saving":[76],"method":[77,143],"for":[78,116],"generation.":[81],"For":[82],"first":[84],"time,":[85],"conduct":[87],"systematic":[88],"investigations":[89],"to":[90,131,150,164],"show":[91],"that":[92],"there":[93],"exist":[94],"severe":[95],"contradictions":[96],"between":[97],"different":[98,127],"types":[99],"target":[101,134,154],"quality,":[102],"namely":[103],"distribution":[104,146],"gap":[105],"(DG).":[106],"To":[107],"bridge":[108],"gap,":[110],"novel":[114],"framework":[115],"training":[117],"combining":[121],"merits":[123],"from":[126,136,167],"sources.":[128],"order":[130],"make":[132],"score":[135],"multiple":[137],"sources":[138],"compatible,":[139],"design":[141],"called":[144],"alignment":[147],"(QDA).":[148],"Meanwhile,":[149],"correct":[151],"models,":[157],"contradictory":[158],"samples":[159,166],"selection":[160],"(CSS)":[161],"is":[162],"adopted":[163],"select":[165],"dataset":[171],"adaptively.":[172],"Extensive":[173],"experiments":[174],"and":[175,192],"analysis":[176],"on":[177],"public":[178],"benchmarks":[179],"including":[180],"MegaFace":[181],"has":[182],"demonstrated":[183],"superiority":[185],"our":[187],"in":[188],"terms":[189],"effectiveness":[191],"efficiency.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
