{"id":"https://openalex.org/W4210487887","doi":"https://doi.org/10.1109/fg52635.2021.9666944","title":"Supervised Contrastive Learning for Facial Kinship Recognition","display_name":"Supervised Contrastive Learning for Facial Kinship Recognition","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4210487887","doi":"https://doi.org/10.1109/fg52635.2021.9666944"},"language":"en","primary_location":{"id":"doi:10.1109/fg52635.2021.9666944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9666944","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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/A5020923609","display_name":"Ximiao Zhang","orcid":"https://orcid.org/0000-0002-6450-0915"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ximiao Zhang","raw_affiliation_strings":["Information Engineering College, Capital Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering College, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102008834","display_name":"Min Xu","orcid":"https://orcid.org/0000-0002-9784-5792"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min XU","raw_affiliation_strings":["Information Engineering College, Capital Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Engineering College, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085431435","display_name":"Xiuzhuang Zhou","orcid":"https://orcid.org/0000-0003-1458-4118"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuzhuang Zhou","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085022758","display_name":"Guodong Guo","orcid":"https://orcid.org/0000-0001-9583-0055"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodong Guo","raw_affiliation_strings":["Institute of Deep Learning, Baidu Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Deep Learning, Baidu Research, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020923609"],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":null,"apc_paid":null,"fwci":0.3267,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.70434908,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"05"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9991000294685364,"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":0.9991000294685364,"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/T11374","display_name":"Cleft Lip and Palate Research","score":0.9740999937057495,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kinship","display_name":"Kinship","score":0.9520958662033081},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7148435115814209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6734987497329712},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6416329145431519},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5665624141693115},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.498518705368042},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48080936074256897},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4689677953720093},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4491274058818817},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4336233139038086},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4168773293495178},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17119470238685608},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14528167247772217},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10848826169967651}],"concepts":[{"id":"https://openalex.org/C144348335","wikidata":"https://www.wikidata.org/wiki/Q171318","display_name":"Kinship","level":2,"score":0.9520958662033081},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7148435115814209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6734987497329712},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6416329145431519},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5665624141693115},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.498518705368042},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48080936074256897},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4689677953720093},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4491274058818817},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4336233139038086},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4168773293495178},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17119470238685608},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14528167247772217},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10848826169967651},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg52635.2021.9666944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9666944","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1996337501","https://openalex.org/W1998230826","https://openalex.org/W2012783213","https://openalex.org/W2112999064","https://openalex.org/W2187089797","https://openalex.org/W2514748494","https://openalex.org/W2520903215","https://openalex.org/W2524441125","https://openalex.org/W2679426462","https://openalex.org/W2765344304","https://openalex.org/W2797200251","https://openalex.org/W2938731855","https://openalex.org/W2969985801","https://openalex.org/W3005680577","https://openalex.org/W3036295637","https://openalex.org/W3105535737","https://openalex.org/W3127190687","https://openalex.org/W3127722966","https://openalex.org/W3128708829","https://openalex.org/W3128844413","https://openalex.org/W3134575743","https://openalex.org/W3141334570","https://openalex.org/W4287812705","https://openalex.org/W6681440187","https://openalex.org/W6727521859","https://openalex.org/W6773471076","https://openalex.org/W6774314701","https://openalex.org/W6776700526","https://openalex.org/W6778926959","https://openalex.org/W6780186611"],"related_works":["https://openalex.org/W1579373186","https://openalex.org/W4312685612","https://openalex.org/W4317827232","https://openalex.org/W2890085216","https://openalex.org/W2046291598","https://openalex.org/W2504703202","https://openalex.org/W1708418756","https://openalex.org/W2976679446","https://openalex.org/W1967293071","https://openalex.org/W2384651879"],"abstract_inverted_index":{"Vision-based":[0],"kinship":[1,20,71,88,92],"recognition":[2,21,72,89],"aims":[3],"to":[4,15,32,84],"determine":[5],"whether":[6],"the":[7,18,24,59,101,105,118,123,126],"face":[8],"images":[9],"have":[10,23],"a":[11,65,79],"kin":[12],"relation.":[13],"Compared":[14],"traditional":[16],"solutions,":[17],"vision-based":[19],"methods":[22],"advantages":[25],"of":[26,43,52,69,113,125],"lower":[27],"cost":[28],"and":[29,49,96],"being":[30],"easy":[31],"implement.":[33],"Therefore,":[34],"such":[35],"technique":[36],"can":[37],"be":[38],"widely":[39],"employed":[40],"in":[41,58,100],"lots":[42],"scenarios":[44],"including":[45],"missing":[46],"children":[47],"search":[48],"automatic":[50],"management":[51],"family":[53],"album.":[54],"The":[55],"Recognizing":[56],"Families":[57],"Wild":[60],"(RFIW)":[61],"Data":[62],"Challenge":[63],"provides":[64],"platform":[66],"for":[67],"evaluation":[68],"different":[70,87],"approaches":[73],"with":[74,104],"ranked":[75],"results.":[76],"We":[77],"propose":[78],"supervised":[80],"contrastive":[81],"learning":[82],"approach":[83],"address":[85],"three":[86,111],"tracks":[90,112],"(i.e.,":[91],"verification,":[93,95],"tri-subject":[94],"large-scale":[97],"search-and-retrieval)":[98],"announced":[99],"RFIW":[102,115],"2021":[103,106,114],"FG.":[107],"Our":[108],"results":[109],"on":[110],"challenge":[116],"achieve":[117],"highest":[119],"ranking,":[120],"which":[121],"demonstrate":[122],"superiority":[124],"proposed":[127],"solution.":[128]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}