{"id":"https://openalex.org/W4403577364","doi":"https://doi.org/10.1145/3627673.3679737","title":"FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition","display_name":"FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403577364","doi":"https://doi.org/10.1145/3627673.3679737"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679737","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","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/A5045401193","display_name":"Ziyi Kou","orcid":"https://orcid.org/0000-0002-9916-0930"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ziyi Kou","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057838053","display_name":"Yijun Tian","orcid":"https://orcid.org/0000-0003-2795-6080"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yijun Tian","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074821819","display_name":"Meng Jiang","orcid":"https://orcid.org/0000-0002-3009-519X"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Meng Jiang","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000755750","display_name":"Xiangliang Zhang","orcid":"https://orcid.org/0000-0002-3574-5665"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangliang Zhang","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045401193"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":0.2493,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54194188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1121","last_page":"1131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9958000183105469,"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":0.954800009727478,"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/facial-recognition-system","display_name":"Facial recognition system","score":0.7594339847564697},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.70304936170578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955379843711853},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.647466778755188},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.44271156191825867},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4043804407119751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3957196772098541},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.27069026231765747},{"id":"https://openalex.org/keywords/aesthetics","display_name":"Aesthetics","score":0.11695614457130432},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.071205735206604},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.06970280408859253}],"concepts":[{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7594339847564697},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.70304936170578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955379843711853},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.647466778755188},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.44271156191825867},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4043804407119751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3957196772098541},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27069026231765747},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.11695614457130432},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.071205735206604},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.06970280408859253},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679737","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W610324613","https://openalex.org/W2048154471","https://openalex.org/W2096733369","https://openalex.org/W2108598243","https://openalex.org/W2111380184","https://openalex.org/W2115252128","https://openalex.org/W2159024459","https://openalex.org/W2194775991","https://openalex.org/W2255364744","https://openalex.org/W2491457278","https://openalex.org/W2506827921","https://openalex.org/W2612430715","https://openalex.org/W2767150422","https://openalex.org/W2969985801","https://openalex.org/W2972163947","https://openalex.org/W2982340830","https://openalex.org/W2989505547","https://openalex.org/W3119994080","https://openalex.org/W3120485916","https://openalex.org/W3172415559","https://openalex.org/W3175129878","https://openalex.org/W3185350140","https://openalex.org/W3190790101","https://openalex.org/W3198014238","https://openalex.org/W3203636625","https://openalex.org/W4214835294","https://openalex.org/W4224311101","https://openalex.org/W4304014846","https://openalex.org/W4312497550","https://openalex.org/W4312933868","https://openalex.org/W4367046779","https://openalex.org/W4375928872","https://openalex.org/W4385801729"],"related_works":["https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2379932303","https://openalex.org/W2095239294","https://openalex.org/W3147744369","https://openalex.org/W2062586268","https://openalex.org/W2019582947","https://openalex.org/W3212688212","https://openalex.org/W4300873085","https://openalex.org/W2384651879"],"abstract_inverted_index":{"Current":[0],"face":[1,51,60,81,94,108,117,123,131,145,179,216],"recognition":[2],"(FR)":[3],"algorithms":[4],"frequently":[5],"encounter":[6],"discrimination":[7],"issues":[8],"in":[9],"terms":[10],"of":[11,23,57,69,96,168,202,214],"various":[12,187],"attributes":[13],"(e.g.,":[14],"gender,":[15],"age)":[16],"due":[17],"to":[18,45,143],"the":[19,24,42,47,55,58,67,79,90,93,97,102,141,153,165,169,203,212],"biased":[20,116],"demographic":[21,127,161,188],"distribution":[22,162],"training":[25],"datasets":[26,48,119],"towards":[27],"specific":[28,122],"groups.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,104],"study":[34],"an":[35],"identity":[36,111,136],"protected":[37],"fair":[38],"FR":[39,85,171,205],"problem":[40,63],"where":[41],"goal":[43],"is":[44,64,156],"augment":[46],"with":[49,125,134,147],"external":[50,80,130,215],"images":[52,82,132,146],"while":[53,88,207],"ensuring":[54],"anonymity":[56,210],"corresponding":[59],"identities.":[61,149],"Our":[62],"motivated":[65],"by":[66,84,120],"limitation":[68],"current":[70],"fairness":[71,166,198],"driven":[72,110],"data":[73],"augmentation":[74],"approaches":[75],"that":[76,114,184,193],"directly":[77],"utilize":[78],"accessed":[83],"algorithm":[86],"developers":[87],"ignoring":[89],"protection":[91],"on":[92,176],"identities":[95,213],"image":[98,118],"owners.":[99],"To":[100],"address":[101],"problem,":[103],"develop":[105],"FaDE,":[106],"a":[107,151,158],"segment":[109],"anonymization":[112],"framework":[113],"augments":[115],"identifying":[121],"segments":[124,142],"diversified":[126],"characteristics":[128],"from":[129,186],"but":[133],"least":[135],"disclosure,":[137],"and":[138,163,182,199],"then":[139],"reconstructing":[140],"full":[144],"new":[148],"As":[150],"result,":[152],"augmented":[154],"dataset":[155],"under":[157],"more":[159],"balanced":[160],"improves":[164],"performance":[167,201],"optimized":[170,204],"algorithms.":[172],"We":[173],"evaluate":[174],"FaDE":[175,194],"two":[177],"public":[178],"datasets,":[180],"CelebA":[181],"LFW":[183],"suffer":[185],"imbalance.":[189],"The":[190],"results":[191],"show":[192],"significantly":[195],"enhances":[196],"both":[197],"accuracy":[200],"algorithms,":[206],"keeping":[208],"effective":[209],"for":[211],"images.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}