{"id":"https://openalex.org/W7131070028","doi":"https://doi.org/10.1109/iccvw69036.2025.00796","title":"Fairness without Labels: Pseudo-Balancing for Bias Mitigation in Face Gender Classification","display_name":"Fairness without Labels: Pseudo-Balancing for Bias Mitigation in Face Gender Classification","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W7131070028","doi":"https://doi.org/10.1109/iccvw69036.2025.00796"},"language":"en","primary_location":{"id":"doi:10.1109/iccvw69036.2025.00796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-05210445v1/file/FAILED-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126620602","display_name":"Haohua Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haohua Dong","raw_affiliation_strings":["National Institute of Informatics,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics,Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109065443","display_name":"Ana Manzano Rodriguez","orcid":"https://orcid.org/0009-0006-6849-6294"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ana Manzano Rodr\u00edguez","raw_affiliation_strings":["National Institute of Informatics,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics,Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037286036","display_name":"Camille Guinaudeau","orcid":"https://orcid.org/0000-0001-7249-8715"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Camille Guinaudeau","raw_affiliation_strings":["Université Paris-Saclay,LIMSI, CNRS,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Université Paris-Saclay,LIMSI, CNRS,France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102743927","display_name":"Shin\u2019ichi Satoh","orcid":"https://orcid.org/0000-0001-6995-6447"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin'ichi Satoh","raw_affiliation_strings":["National Institute of Informatics,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics,Japan","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.76112796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7733","last_page":"7742"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.4661000072956085,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.4661000072956085,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11118","display_name":"Evolutionary Psychology and Human Behavior","score":0.1370999962091446,"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"}},{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.032999999821186066,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/debiasing","display_name":"Debiasing","score":0.9020000100135803},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5760999917984009},{"id":"https://openalex.org/keywords/gender-bias","display_name":"Gender bias","score":0.5424000024795532},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5012000203132629},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4397999942302704},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4203000068664551},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4043000042438507}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.9020000100135803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6141999959945679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6044999957084656},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5760999917984009},{"id":"https://openalex.org/C2983427547","wikidata":"https://www.wikidata.org/wiki/Q93200","display_name":"Gender bias","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4943000078201294},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4397999942302704},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4043000042438507},{"id":"https://openalex.org/C2993152109","wikidata":"https://www.wikidata.org/wiki/Q1068155","display_name":"Gender balance","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2897999882698059},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.27900001406669617},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C2986619947","wikidata":"https://www.wikidata.org/wiki/Q30103150","display_name":"Gender gap","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C76509639","wikidata":"https://www.wikidata.org/wiki/Q918036","display_name":"Race (biology)","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C3019252630","wikidata":"https://www.wikidata.org/wiki/Q6549547","display_name":"Limited resources","level":2,"score":0.2623000144958496}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccvw69036.2025.00796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-05210445v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05210445","pdf_url":"https://hal.science/hal-05210445v1/file/FAILED-3.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://2nd-failed-workshop-iccv-2025.github.io/","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-05210445v1","is_oa":true,"landing_page_url":"https://hal.science/hal-05210445","pdf_url":"https://hal.science/hal-05210445v1/file/FAILED-3.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://2nd-failed-workshop-iccv-2025.github.io/","raw_type":"Conference papers"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.7677031755447388,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7131070028.pdf","grobid_xml":"https://content.openalex.org/works/W7131070028.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1731081199","https://openalex.org/W1997011019","https://openalex.org/W2014352947","https://openalex.org/W2069705645","https://openalex.org/W2145287260","https://openalex.org/W2194775991","https://openalex.org/W2403084738","https://openalex.org/W2895281799","https://openalex.org/W2895907079","https://openalex.org/W2913691781","https://openalex.org/W2962787423","https://openalex.org/W3035160371","https://openalex.org/W3035524453","https://openalex.org/W3037594484","https://openalex.org/W3110002552","https://openalex.org/W3120485916","https://openalex.org/W3181414820","https://openalex.org/W3204140421","https://openalex.org/W4385597536"],"related_works":[],"abstract_inverted_index":{"Face":[0],"gender":[1,20,71,139],"classification":[2],"models":[3,98],"often":[4],"reflect":[5],"and":[6,21,29,80],"amplify":[7],"demographic":[8,42],"biases":[9,35],"present":[10],"in":[11,36,166],"their":[12],"training":[13,88],"data,":[14],"leading":[15],"to":[16,58,90,158,173],"uneven":[17],"performance":[18],"across":[19],"racial":[22],"sub-groups.":[23],"We":[24,61],"introduce":[25],"pseudo-balancing,":[26],"a":[27,52,69,108,174,185],"simple":[28],"effective":[30],"strategy":[31],"for":[32,188],"mitigating":[33],"such":[34],"semi-supervised":[37],"learning.":[38],"Our":[39,113],"method":[40,84,127],"enforces":[41],"balance":[43],"during":[44],"pseudo-label":[45],"selection,":[46],"using":[47,73],"only":[48],"unlabeled":[49,74,180],"images":[50,75],"from":[51,76],"race-balanced":[53],"dataset":[54,181],"without":[55],"requiring":[56],"access":[57,172],"ground-truth":[59],"annotations.":[60],"evaluate":[62],"pseudo-balancing":[63,117],"under":[64],"two":[65],"conditions:":[66],"(1)":[67],"fine-tuning":[68],"biased":[70],"classifier":[72],"the":[77,83,102,135,138,145,154,167],"FairFace":[78],"dataset,":[79],"(2)":[81],"stress-testing":[82],"with":[85],"intentionally":[86],"imbalanced":[87],"data":[89],"simulate":[91],"controlled":[92],"bias":[93],"scenarios.":[94],"In":[95,144],"both":[96],"cases,":[97],"are":[99],"evaluated":[100],"on":[101],"All-Age-Faces":[103],"(AAF)":[104],"benchmark,":[105],"which":[106],"contains":[107],"predominantly":[109],"East":[110,146],"Asian":[111,147],"population.":[112],"results":[114],"show":[115],"that":[116,164],"consistently":[118],"improves":[119],"fairness":[120],"while":[121],"preserving":[122],"or":[123,177],"enhancing":[124],"accuracy.":[125],"The":[126],"achieves":[128],"79.81%":[129],"overall":[130],"accuracy\u2014a":[131],"6.53%":[132],"improvement":[133],"over":[134],"baseline\u2014and":[136],"reduces":[137],"accuracy":[140],"gap":[141,155],"by":[142],"44.17%.":[143],"subgroup,":[148],"where":[149],"baseline":[150],"disparities":[151],"exceeded":[152],"49%,":[153],"is":[156],"narrowed":[157],"just":[159],"5.01%.":[160],"These":[161],"findings":[162],"suggest":[163],"even":[165],"absence":[168],"of":[169],"label":[170],"supervision,":[171],"demographically":[175],"balanced":[176],"moderately":[178],"skewed":[179],"can":[182],"serve":[183],"as":[184],"powerful":[186],"resource":[187],"debiasing":[189],"existing":[190],"computer":[191],"vision":[192],"models.":[193]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-24T00:00:00"}