{"id":"https://openalex.org/W3000557356","doi":"https://doi.org/10.1109/tmm.2020.2966863","title":"An Equalized Margin Loss for Face Recognition","display_name":"An Equalized Margin Loss for Face Recognition","publication_year":2020,"publication_date":"2020-01-15","ids":{"openalex":"https://openalex.org/W3000557356","doi":"https://doi.org/10.1109/tmm.2020.2966863","mag":"3000557356"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2020.2966863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2020.2966863","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10089852/1/TMM-JingnaSun-EqM-UCL.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101718269","display_name":"Jingna Sun","orcid":"https://orcid.org/0000-0001-8415-1102"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingna Sun","raw_affiliation_strings":["Shenzhen Key Laboratory of Information and Science Technology/Shenzhen Engineering Laboratory of Information Security and Digital Content Protection (IS&DCP), Graduate School at Shenzhen/Department of Electronic Engineering, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-8415-1102","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Information and Science Technology/Shenzhen Engineering Laboratory of Information Security and Digital Content Protection (IS&DCP), Graduate School at Shenzhen/Department of Electronic Engineering, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026184280","display_name":"Wenming Yang","orcid":"https://orcid.org/0000-0002-2506-1286"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Yang","raw_affiliation_strings":["Shenzhen Key Laboratory of Information and Science Technology/Shenzhen Engineering Laboratory of Information Security and Digital Content Protection (IS&DCP), Graduate School at Shenzhen/Department of Electronic Engineering, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2506-1286","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Information and Science Technology/Shenzhen Engineering Laboratory of Information Security and Digital Content Protection (IS&DCP), Graduate School at Shenzhen/Department of Electronic Engineering, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079361172","display_name":"Jing\u2010Hao Xue","orcid":"https://orcid.org/0000-0003-1174-610X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jing-Hao Xue","raw_affiliation_strings":["Department of Statistical Science, University College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1174-610X","affiliations":[{"raw_affiliation_string":"Department of Statistical Science, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009239895","display_name":"Qingmin Liao","orcid":"https://orcid.org/0000-0002-7509-3964"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingmin Liao","raw_affiliation_strings":["Shenzhen Key Laboratory of Information and Science Technology/Shenzhen Engineering Laboratory of Information Security and Digital Content Protection (IS&DCP), Graduate School at Shenzhen/Department of Electronic Engineering, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Information and Science Technology/Shenzhen Engineering Laboratory of Information Security and Digital Content Protection (IS&DCP), Graduate School at Shenzhen/Department of Electronic Engineering, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101718269"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.4718,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.84310962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"22","issue":"11","first_page":"2833","last_page":"2843"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"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":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.796351432800293},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7062420845031738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6984917521476746},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6877891421318054},{"id":"https://openalex.org/keywords/hypersphere","display_name":"Hypersphere","score":0.6636461615562439},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5795491337776184},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.579127311706543},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5090839266777039},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4641585946083069},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45215484499931335},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4396968483924866},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43257856369018555},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.41686826944351196},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3731826841831207},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2845790982246399},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2535405158996582},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22663047909736633}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.796351432800293},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7062420845031738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984917521476746},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6877891421318054},{"id":"https://openalex.org/C2776562905","wikidata":"https://www.wikidata.org/wiki/Q306610","display_name":"Hypersphere","level":2,"score":0.6636461615562439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5795491337776184},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.579127311706543},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5090839266777039},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4641585946083069},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45215484499931335},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4396968483924866},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43257856369018555},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.41686826944351196},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3731826841831207},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2845790982246399},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2535405158996582},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22663047909736633},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmm.2020.2966863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2020.2966863","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10089852","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10089852/","pdf_url":"https://discovery.ucl.ac.uk/10089852/1/TMM-JingnaSun-EqM-UCL.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Transactions on Multimedia       (2020)     (In press).  ","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10089852","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10089852/","pdf_url":"https://discovery.ucl.ac.uk/10089852/1/TMM-JingnaSun-EqM-UCL.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Transactions on Multimedia       (2020)     (In press).  ","raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3000557356.pdf","grobid_xml":"https://content.openalex.org/works/W3000557356.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W1509966554","https://openalex.org/W1677182931","https://openalex.org/W1782590233","https://openalex.org/W1899185266","https://openalex.org/W1951319388","https://openalex.org/W1970748944","https://openalex.org/W1998808035","https://openalex.org/W2016053056","https://openalex.org/W2019464758","https://openalex.org/W2024922353","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2121199413","https://openalex.org/W2121647436","https://openalex.org/W2157323699","https://openalex.org/W2167144347","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2341528187","https://openalex.org/W2404498690","https://openalex.org/W2440599146","https://openalex.org/W2515770085","https://openalex.org/W2520774990","https://openalex.org/W2560205181","https://openalex.org/W2560473673","https://openalex.org/W2600537992","https://openalex.org/W2609575245","https://openalex.org/W2736633948","https://openalex.org/W2737608545","https://openalex.org/W2751862348","https://openalex.org/W2752042386","https://openalex.org/W2775447965","https://openalex.org/W2781292787","https://openalex.org/W2784163702","https://openalex.org/W2784294927","https://openalex.org/W2906760449","https://openalex.org/W2962898354","https://openalex.org/W2962922273","https://openalex.org/W2963224870","https://openalex.org/W2963325056","https://openalex.org/W2963351448","https://openalex.org/W2963466847","https://openalex.org/W2963656735","https://openalex.org/W2963671154","https://openalex.org/W2963968551","https://openalex.org/W2963996492","https://openalex.org/W2969985801","https://openalex.org/W2973161808","https://openalex.org/W3099206234","https://openalex.org/W3101227480","https://openalex.org/W3101998545","https://openalex.org/W3102661353","https://openalex.org/W3103152812","https://openalex.org/W4293478066","https://openalex.org/W6630649318","https://openalex.org/W6639927594","https://openalex.org/W6677936389","https://openalex.org/W6726946684","https://openalex.org/W6735013348","https://openalex.org/W6743520202","https://openalex.org/W6748010250","https://openalex.org/W6751593755","https://openalex.org/W6757321189","https://openalex.org/W6842019321","https://openalex.org/W6891715281"],"related_works":["https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W2609296554","https://openalex.org/W2963466847","https://openalex.org/W3128220219","https://openalex.org/W2982889384","https://openalex.org/W4226227567","https://openalex.org/W2971218105","https://openalex.org/W3006353185","https://openalex.org/W3010284783"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,77,129],"propose":[4],"a":[5],"new":[6],"loss":[7,48,105,146],"function,":[8],"termed":[9],"the":[10,33,40,43,51,62,74,88,92,96,103,109,112,134,139],"equalized":[11,70],"margin":[12],"(EqM)":[13],"loss,":[14,76,141],"which":[15],"is":[16,106],"designed":[17],"to":[18,132],"make":[19],"both":[20,50],"intra-class":[21,55],"scopes":[22],"and":[23,61,127,136],"inter-class":[24,66,97],"margins":[25],"similar":[26],"over":[27],"all":[28,32],"classes,":[29],"such":[30],"that":[31,102],"classes":[34],"can":[35,78],"be":[36],"evenly":[37],"distributed":[38],"on":[39,95,122],"hypersphere":[41],"of":[42,54,65,111,138],"feature":[44],"space.":[45],"The":[46],"EqM":[47,75,104,140],"controls":[49],"lower":[52],"limit":[53,64],"similarity":[56,67],"by":[57,68,118],"exploiting":[58],"hard-sample":[59],"mining":[60],"upper":[63],"assuring":[69],"margins.":[71,98],"Therefore,":[72],"using":[73],"not":[79],"only":[80],"obtain":[81],"more":[82],"discriminative":[83],"features,":[84],"but":[85],"also":[86,100],"overcome":[87],"negative":[89],"impacts":[90],"from":[91],"data":[93],"imbalance":[94],"We":[99],"observe":[101],"stable":[107],"with":[108,143],"variation":[110],"scale":[113],"in":[114],"normalized":[115],"Softmax.":[116],"Furthermore,":[117],"conducting":[119],"extensive":[120],"experiments":[121],"LFW,":[123],"YTF,":[124],"CFP,":[125],"MegaFace":[126],"IJB-B,":[128],"are":[130],"able":[131],"verify":[133],"effectiveness":[135],"superiority":[137],"compared":[142],"other":[144],"state-of-the-art":[145],"functions":[147],"for":[148],"face":[149],"recognition.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
