{"id":"https://openalex.org/W4413120800","doi":"https://doi.org/10.1109/tifs.2025.3597187","title":"From Age Estimation to Age-Invariant Face Recognition: Generalized Age Feature Extraction Using Order-Enhanced Contrastive Learning","display_name":"From Age Estimation to Age-Invariant Face Recognition: Generalized Age Feature Extraction Using Order-Enhanced Contrastive Learning","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413120800","doi":"https://doi.org/10.1109/tifs.2025.3597187"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2025.3597187","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3597187","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-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/A5101815492","display_name":"Haoyi Wang","orcid":"https://orcid.org/0000-0001-6465-8096"},"institutions":[{"id":"https://openalex.org/I897542642","display_name":"University of Plymouth","ror":"https://ror.org/008n7pv89","country_code":"GB","type":"education","lineage":["https://openalex.org/I897542642"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Haoyi Wang","raw_affiliation_strings":["School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, U.K","School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, U.K","institution_ids":["https://openalex.org/I897542642"]},{"raw_affiliation_string":"School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, UK","institution_ids":["https://openalex.org/I897542642"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100634965","display_name":"V\u00edctor S\u00e1nchez","orcid":"https://orcid.org/0000-0002-7089-7031"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Victor Sanchez","raw_affiliation_strings":["Department of Computer Science, University of Warwick, Coventry, U.K","Department of Computer Science, University of Warwick, Coventry, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Warwick, Coventry, U.K","institution_ids":["https://openalex.org/I39555362"]},{"raw_affiliation_string":"Department of Computer Science, University of Warwick, Coventry, UK","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075200053","display_name":"Chang\u2010Tsun Li","orcid":"https://orcid.org/0000-0003-4735-6138"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chang-Tsun Li","raw_affiliation_strings":["School of Information Technology, Deakin University, Geelong, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029670131","display_name":"Nathan Clarke","orcid":"https://orcid.org/0000-0002-3595-3800"},"institutions":[{"id":"https://openalex.org/I897542642","display_name":"University of Plymouth","ror":"https://ror.org/008n7pv89","country_code":"GB","type":"education","lineage":["https://openalex.org/I897542642"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nathan Clarke","raw_affiliation_strings":["School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, U.K","School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, U.K","institution_ids":["https://openalex.org/I897542642"]},{"raw_affiliation_string":"School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, UK","institution_ids":["https://openalex.org/I897542642"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101815492"],"corresponding_institution_ids":["https://openalex.org/I897542642"],"apc_list":null,"apc_paid":null,"fwci":2.66,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.90974181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"20","issue":null,"first_page":"8525","last_page":"8540"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9984999895095825,"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":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9126999974250793,"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/computer-science","display_name":"Computer science","score":0.7090522050857544},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6951216459274292},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6884532570838928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6198408007621765},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5890239477157593},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5211032629013062},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3572580814361572},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21319666504859924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7090522050857544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6951216459274292},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6884532570838928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6198408007621765},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5890239477157593},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5211032629013062},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3572580814361572},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21319666504859924},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tifs.2025.3597187","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3597187","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-article"},{"id":"pmh:oai:wrap.warwick.ac.uk:194496","is_oa":false,"landing_page_url":"https://doi.org/10.1109/TIFS.2025.3597187","pdf_url":null,"source":{"id":"https://openalex.org/S4306400665","display_name":"Warwick Research Archive Portal (University of Warwick)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39555362","host_organization_name":"University of Warwick","host_organization_lineage":["https://openalex.org/I39555362"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"NonPeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":90,"referenced_works":["https://openalex.org/W1167806532","https://openalex.org/W1972960842","https://openalex.org/W1978675111","https://openalex.org/W1995903905","https://openalex.org/W2030098377","https://openalex.org/W2032454342","https://openalex.org/W2039140324","https://openalex.org/W2065230098","https://openalex.org/W2066454034","https://openalex.org/W2067425370","https://openalex.org/W2103077782","https://openalex.org/W2104320981","https://openalex.org/W2105026179","https://openalex.org/W2111084364","https://openalex.org/W2115651492","https://openalex.org/W2118664399","https://openalex.org/W2146656095","https://openalex.org/W2164715565","https://openalex.org/W2166939233","https://openalex.org/W2194775991","https://openalex.org/W2431335693","https://openalex.org/W2440214111","https://openalex.org/W2469434562","https://openalex.org/W2510725918","https://openalex.org/W2535798196","https://openalex.org/W2557430144","https://openalex.org/W2605102252","https://openalex.org/W2663800299","https://openalex.org/W2736494531","https://openalex.org/W2748140016","https://openalex.org/W2798868324","https://openalex.org/W2807904173","https://openalex.org/W2883320311","https://openalex.org/W2895550533","https://openalex.org/W2896154921","https://openalex.org/W2899762210","https://openalex.org/W2921918732","https://openalex.org/W2941422046","https://openalex.org/W2955216108","https://openalex.org/W2962786991","https://openalex.org/W2962950337","https://openalex.org/W2963115481","https://openalex.org/W2963671154","https://openalex.org/W2963767627","https://openalex.org/W2971130703","https://openalex.org/W2971228604","https://openalex.org/W3003383851","https://openalex.org/W3003442407","https://openalex.org/W3003536578","https://openalex.org/W3014895431","https://openalex.org/W3034202663","https://openalex.org/W3035524453","https://openalex.org/W3038218176","https://openalex.org/W3043978417","https://openalex.org/W3092466816","https://openalex.org/W3145450063","https://openalex.org/W3171007011","https://openalex.org/W3175713115","https://openalex.org/W3200886401","https://openalex.org/W3201733951","https://openalex.org/W4205250574","https://openalex.org/W4206349370","https://openalex.org/W4206687860","https://openalex.org/W4281662861","https://openalex.org/W4296894930","https://openalex.org/W4312501338","https://openalex.org/W4362454698","https://openalex.org/W4375928872","https://openalex.org/W4387068049","https://openalex.org/W4387457448","https://openalex.org/W4390872643","https://openalex.org/W4391946607","https://openalex.org/W4392902684","https://openalex.org/W4400037174","https://openalex.org/W4402205674","https://openalex.org/W4402727470","https://openalex.org/W4404893185","https://openalex.org/W4406983007","https://openalex.org/W4407598818","https://openalex.org/W4413157642","https://openalex.org/W6639480849","https://openalex.org/W6677618333","https://openalex.org/W6772079387","https://openalex.org/W6774670964","https://openalex.org/W6776700526","https://openalex.org/W6796584642","https://openalex.org/W6803308325","https://openalex.org/W6845076884","https://openalex.org/W6853754985","https://openalex.org/W6967038676"],"related_works":["https://openalex.org/W2116423617","https://openalex.org/W2347824352","https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2112875849","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640"],"abstract_inverted_index":{"Generalized":[0],"age":[1,13,44,56,145,205,229],"feature":[2],"extraction":[3],"is":[4],"crucial":[5],"for":[6,84,203,227,237],"age-related":[7],"facial":[8],"analysis":[9],"tasks,":[10],"such":[11],"as":[12,46,130],"estimation":[14,206,230],"and":[15,151,177,207,232],"age-invariant":[16],"face":[17],"recognition":[18],"(AIFR).":[19],"Despite":[20],"the":[21,62,96,104,113,141,159,162,169,174,179,218,228,234],"recent":[22],"successes":[23],"of":[24,37,66,99,116,143,171,181],"models":[25,39],"in":[26,33,200],"homogeneous-dataset":[27,201],"experiments,":[28,211],"their":[29],"performance":[30],"drops":[31],"significantly":[32],"cross-dataset":[34,210],"evaluations.":[35],"Most":[36],"these":[38],"fail":[40],"to":[41,50,90,111,193],"extract":[42,91],"generalized":[43,92],"features":[45,53,101,137],"they":[47],"only":[48],"attempt":[49],"map":[51],"extracted":[52],"with":[54,102,147],"training":[55],"labels":[57],"directly":[58],"without":[59],"explicitly":[60,83],"modeling":[61,158],"natural":[63,105],"ordinal":[64,85,114],"progression":[65],"aging.":[67,117],"In":[68,209],"this":[69],"paper,":[70],"we":[71],"propose":[72],"Order-Enhanced":[73],"Contrastive":[74],"Learning":[75],"(OrdCon),":[76],"a":[77,124,131],"novel":[78,125],"contrastive":[79,133],"learning":[80],"framework":[81,163],"designed":[82],"attributes":[86],"like":[87],"age.":[88],"Specifically,":[89],"features,":[93],"OrdCon":[94,122,212],"aligns":[95],"direction":[97,107,182],"vector":[98],"two":[100],"either":[103],"aging":[106],"or":[108],"its":[109],"reverse":[110],"model":[112],"process":[115],"To":[118],"further":[119],"enhance":[120,165],"generalizability,":[121],"leverages":[123],"soft":[126],"proxy":[127],"matching":[128],"loss":[129],"second":[132],"objective,":[134],"ensuring":[135],"that":[136,186],"are":[138],"positioned":[139],"around":[140],"center":[142],"each":[144],"cluster":[146],"minimal":[148],"intra-class":[149],"variance":[150],"proportionally":[152],"away":[153],"from":[154,173],"other":[155,214],"clusters.":[156],"By":[157],"ageing":[160],"process,":[161],"can":[164],"generalizability":[166],"by":[167,216,222,239],"improving":[168],"alignment":[170],"samples":[172],"same":[175],"class":[176],"reducing":[178,217],"divergence":[180],"vectors.":[183],"We":[184],"demonstrate":[185],"our":[187],"proposed":[188],"method":[189],"achieves":[190],"comparable":[191],"results":[192],"state-of-the-art":[194],"methods":[195,215],"on":[196,225],"various":[197],"benchmark":[198],"datasets":[199],"evaluations":[202],"both":[204],"AIFR.":[208],"outperforms":[213],"mean":[219],"absolute":[220],"error":[221],"approximately":[223],"1.38":[224],"average":[226,235],"task":[231],"boosts":[233],"accuracy":[236],"AIFR":[238],"1.87%.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
