{"id":"https://openalex.org/W4386072502","doi":"https://doi.org/10.23919/mva57639.2023.10216074","title":"Age Prediction From Face Images Via Contrastive Learning","display_name":"Age Prediction From Face Images Via Contrastive Learning","publication_year":2023,"publication_date":"2023-07-23","ids":{"openalex":"https://openalex.org/W4386072502","doi":"https://doi.org/10.23919/mva57639.2023.10216074"},"language":"en","primary_location":{"id":"doi:10.23919/mva57639.2023.10216074","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/mva57639.2023.10216074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 18th International Conference on Machine Vision and Applications (MVA)","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/A5023201501","display_name":"Yeongnam Chae","orcid":"https://orcid.org/0000-0002-2996-1759"},"institutions":[{"id":"https://openalex.org/I1301041018","display_name":"Rakuten (Japan)","ror":"https://ror.org/0098kke80","country_code":"JP","type":"company","lineage":["https://openalex.org/I1301041018"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yeongnam Chae","raw_affiliation_strings":["Rakuten Group, Inc.,Rakuten Institute of Technology","Rakuten Institute of Technology, Rakuten Group, Inc"],"affiliations":[{"raw_affiliation_string":"Rakuten Group, Inc.,Rakuten Institute of Technology","institution_ids":["https://openalex.org/I1301041018"]},{"raw_affiliation_string":"Rakuten Institute of Technology, Rakuten Group, Inc","institution_ids":["https://openalex.org/I1301041018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008510029","display_name":"Poulami Raha","orcid":null},"institutions":[{"id":"https://openalex.org/I1301041018","display_name":"Rakuten (Japan)","ror":"https://ror.org/0098kke80","country_code":"JP","type":"company","lineage":["https://openalex.org/I1301041018"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Poulami Raha","raw_affiliation_strings":["Rakuten Group, Inc.,Rakuten Institute of Technology","Rakuten Institute of Technology, Rakuten Group, Inc"],"affiliations":[{"raw_affiliation_string":"Rakuten Group, Inc.,Rakuten Institute of Technology","institution_ids":["https://openalex.org/I1301041018"]},{"raw_affiliation_string":"Rakuten Institute of Technology, Rakuten Group, Inc","institution_ids":["https://openalex.org/I1301041018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100770931","display_name":"Mijung Kim","orcid":"https://orcid.org/0000-0003-3995-5384"},"institutions":[{"id":"https://openalex.org/I1301041018","display_name":"Rakuten (Japan)","ror":"https://ror.org/0098kke80","country_code":"JP","type":"company","lineage":["https://openalex.org/I1301041018"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mijung Kim","raw_affiliation_strings":["Rakuten Group, Inc.,Rakuten Institute of Technology","Rakuten Institute of Technology, Rakuten Group, Inc"],"affiliations":[{"raw_affiliation_string":"Rakuten Group, Inc.,Rakuten Institute of Technology","institution_ids":["https://openalex.org/I1301041018"]},{"raw_affiliation_string":"Rakuten Institute of Technology, Rakuten Group, Inc","institution_ids":["https://openalex.org/I1301041018"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079475252","display_name":"Bj\u00f6rn Stenger","orcid":"https://orcid.org/0009-0008-0465-5545"},"institutions":[{"id":"https://openalex.org/I1301041018","display_name":"Rakuten (Japan)","ror":"https://ror.org/0098kke80","country_code":"JP","type":"company","lineage":["https://openalex.org/I1301041018"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Bj\u00f6rn Stenger","raw_affiliation_strings":["Rakuten Group, Inc.,Rakuten Institute of Technology","Rakuten Institute of Technology, Rakuten Group, Inc"],"affiliations":[{"raw_affiliation_string":"Rakuten Group, Inc.,Rakuten Institute of Technology","institution_ids":["https://openalex.org/I1301041018"]},{"raw_affiliation_string":"Rakuten Institute of Technology, Rakuten Group, Inc","institution_ids":["https://openalex.org/I1301041018"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023201501"],"corresponding_institution_ids":["https://openalex.org/I1301041018"],"apc_list":null,"apc_paid":null,"fwci":0.2429,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52205671,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"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":1.0,"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":0.9919999837875366,"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/T11322","display_name":"Facial Rejuvenation and Surgery Techniques","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2708","display_name":"Dermatology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.8155465722084045},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.7738052606582642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7068166732788086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6847736835479736},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6280746459960938},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6141538023948669},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5602568984031677},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5540030002593994},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5157642364501953},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46700915694236755},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42947378754615784},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18772321939468384}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.8155465722084045},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.7738052606582642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7068166732788086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6847736835479736},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6280746459960938},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6141538023948669},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5602568984031677},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5540030002593994},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5157642364501953},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46700915694236755},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42947378754615784},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18772321939468384},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/mva57639.2023.10216074","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/mva57639.2023.10216074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 18th International Conference on Machine Vision and Applications (MVA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1498305593","https://openalex.org/W1967461346","https://openalex.org/W1971988784","https://openalex.org/W2009088607","https://openalex.org/W2039913439","https://openalex.org/W2061086108","https://openalex.org/W2066808422","https://openalex.org/W2118664399","https://openalex.org/W2118755929","https://openalex.org/W2137802466","https://openalex.org/W2147278565","https://openalex.org/W2163626514","https://openalex.org/W2243756072","https://openalex.org/W2304348237","https://openalex.org/W2341528187","https://openalex.org/W2440214111","https://openalex.org/W2510725918","https://openalex.org/W2515770085","https://openalex.org/W2564173477","https://openalex.org/W2732482952","https://openalex.org/W2748140016","https://openalex.org/W2751572766","https://openalex.org/W2777551880","https://openalex.org/W2798868324","https://openalex.org/W2902046464","https://openalex.org/W2945740428","https://openalex.org/W2955216108","https://openalex.org/W2962786991","https://openalex.org/W2962858109","https://openalex.org/W2962898354","https://openalex.org/W2963466847","https://openalex.org/W2963802733","https://openalex.org/W2969985801","https://openalex.org/W2972367691","https://openalex.org/W2972970563","https://openalex.org/W3035380522","https://openalex.org/W3035693354","https://openalex.org/W3096840866","https://openalex.org/W3099206234","https://openalex.org/W3101998545","https://openalex.org/W3169129566","https://openalex.org/W3205510661","https://openalex.org/W3211843254","https://openalex.org/W4205250574","https://openalex.org/W4312402191","https://openalex.org/W6629622560","https://openalex.org/W6682090056","https://openalex.org/W6726453277","https://openalex.org/W6736780073","https://openalex.org/W6762700047","https://openalex.org/W6785269020","https://openalex.org/W6803840108"],"related_works":["https://openalex.org/W2389818373","https://openalex.org/W2220831889","https://openalex.org/W4312683641","https://openalex.org/W3027421045","https://openalex.org/W2576320324","https://openalex.org/W2980386803","https://openalex.org/W3215994059","https://openalex.org/W2319823519","https://openalex.org/W4206798987","https://openalex.org/W2801158176"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,19,64],"novel":[4],"approach":[5,80],"for":[6],"accurately":[7],"estimating":[8],"age":[9],"from":[10],"face":[11,36],"images,":[12],"which":[13],"overcomes":[14],"the":[15,25,75],"challenge":[16],"of":[17,22,38,66,77],"collecting":[18],"large":[20],"dataset":[21],"individuals":[23],"with":[24],"same":[26],"identity":[27],"at":[28,41],"different":[29,39,42],"ages.":[30],"Instead,":[31],"we":[32],"leverage":[33],"readily":[34],"available":[35],"datasets":[37],"people":[40],"ages":[43],"and":[44,69,90],"aim":[45],"to":[46],"extract":[47],"age-related":[48],"features":[49,58,62],"using":[50,63],"contrastive":[51],"learning.":[52],"Our":[53],"method":[54],"emphasizes":[55],"these":[56],"relevant":[57],"while":[59],"suppressing":[60],"identity-related":[61],"combination":[65],"cosine":[67],"similarity":[68],"triplet":[70],"margin":[71],"losses.":[72],"We":[73],"demonstrate":[74],"effectiveness":[76],"our":[78],"proposed":[79],"by":[81],"achieving":[82],"state-of-the-art":[83],"performance":[84],"on":[85],"two":[86],"public":[87],"datasets,":[88],"FG-NET":[89],"MORPH":[91],"II.":[92]},"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"}
