{"id":"https://openalex.org/W3131893224","doi":"https://doi.org/10.1109/tmm.2021.3057989","title":"TWGAN: Twin Discriminator Generative Adversarial Networks","display_name":"TWGAN: Twin Discriminator Generative Adversarial Networks","publication_year":2021,"publication_date":"2021-02-12","ids":{"openalex":"https://openalex.org/W3131893224","doi":"https://doi.org/10.1109/tmm.2021.3057989","mag":"3131893224"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2021.3057989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3057989","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101694076","display_name":"Zhaoyu Zhang","orcid":"https://orcid.org/0000-0003-4303-2806"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaoyu Zhang","raw_affiliation_strings":["Department of Automation, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078073726","display_name":"Mengyan Li","orcid":"https://orcid.org/0000-0002-7664-4836"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengyan Li","raw_affiliation_strings":["Department of Automation, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108278320","display_name":"Haonian Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haonian Xie","raw_affiliation_strings":["Department of Automation, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048818071","display_name":"Jun Yu","orcid":"https://orcid.org/0000-0002-3197-8103"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Yu","raw_affiliation_strings":["Department of Automation, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065250332","display_name":"Tongliang Liu","orcid":"https://orcid.org/0000-0002-9640-6472"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tongliang Liu","raw_affiliation_strings":["Trustworthy Machine Learning Laboratory, The University of Sydney, Darlington, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Trustworthy Machine Learning Laboratory, The University of Sydney, Darlington, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002277899","display_name":"Chang Wen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang Wen Chen","raw_affiliation_strings":["Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101694076"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":1.0658,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.78461688,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"24","issue":null,"first_page":"677","last_page":"688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9998000264167786,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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/discriminator","display_name":"Discriminator","score":0.9504880905151367},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8999441862106323},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.7243653535842896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6659198999404907},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5573430061340332},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.488102525472641},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.47295042872428894},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.42501503229141235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4222531318664551},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39290812611579895},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37702155113220215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3464909791946411},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23900502920150757}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9504880905151367},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8999441862106323},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.7243653535842896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6659198999404907},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5573430061340332},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.488102525472641},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.47295042872428894},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.42501503229141235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4222531318664551},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39290812611579895},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37702155113220215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3464909791946411},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23900502920150757},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2021.3057989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3057989","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G4938988039","display_name":null,"funder_award_id":"U1736123","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6039323323","display_name":null,"funder_award_id":"61572450","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1571861926","https://openalex.org/W1942762523","https://openalex.org/W2099471712","https://openalex.org/W2194775991","https://openalex.org/W2423557781","https://openalex.org/W2557046619","https://openalex.org/W2566832195","https://openalex.org/W2619903301","https://openalex.org/W2750384547","https://openalex.org/W2791734165","https://openalex.org/W2883334176","https://openalex.org/W2897124202","https://openalex.org/W2911275792","https://openalex.org/W2923549568","https://openalex.org/W2948697666","https://openalex.org/W2963563295","https://openalex.org/W2965141076","https://openalex.org/W2981986999","https://openalex.org/W2994892543","https://openalex.org/W2996570742","https://openalex.org/W3006538026","https://openalex.org/W3008653537","https://openalex.org/W4295274059","https://openalex.org/W6631190155","https://openalex.org/W6677919164","https://openalex.org/W6685352114","https://openalex.org/W6718379498","https://openalex.org/W6729482032","https://openalex.org/W6729993831","https://openalex.org/W6732249622","https://openalex.org/W6735913928","https://openalex.org/W6736155344","https://openalex.org/W6738676538","https://openalex.org/W6743259963","https://openalex.org/W6743446608","https://openalex.org/W6743688258","https://openalex.org/W6743954042","https://openalex.org/W6743994364","https://openalex.org/W6745560452","https://openalex.org/W6748243251","https://openalex.org/W6748582592","https://openalex.org/W6748655329","https://openalex.org/W6752483423","https://openalex.org/W6755312952","https://openalex.org/W6759596418","https://openalex.org/W6765779288","https://openalex.org/W6779669310","https://openalex.org/W6898611122"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2750384547","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W4389249638","https://openalex.org/W2733410219","https://openalex.org/W2734358244","https://openalex.org/W4388700941"],"abstract_inverted_index":{"Generative":[0,84],"Adversarial":[1,85],"Networks":[2,86],"(GAN)":[3],"has":[4,91],"become":[5],"more":[6,8],"and":[7,18,51,94,108,160,186,201,212],"popular":[9],"these":[10],"years.":[11],"However,":[12],"it":[13,47,59],"is":[14,37],"difficult":[15],"to":[16,41,72,113,129,142],"train":[17],"suffers":[19],"from":[20,66,119],"the":[21,55,62,75,116,133,137,144,149,161,175,191,229],"training":[22,76,176],"instability":[23,177],"problem.":[24,178],"To":[25],"tackle":[26],"this":[27,29],"difficulty,":[28],"paper":[30],"proposes":[31],"a":[32,92,95],"novel":[33],"approach.":[34],"Our":[35],"idea":[36],"intuitive":[38],"but":[39],"proven":[40],"be":[42],"very":[43],"useful.":[44],"In":[45],"essence,":[46],"combines":[48],"saturating":[49],"loss":[50,53,56,70],"non-saturating":[52],"into":[54],"function.":[57],"Thus":[58],"will":[60],"exploit":[61],"complementary":[63],"statistical":[64],"properties":[65],"two":[67,103],"kinds":[68],"of":[69,102,110,139,151,163,194,231],"functions":[71],"effectively":[73,173],"improve":[74],"stability.":[77],"We":[78,125],"term":[79],"our":[80,195,232],"method":[81],"twin":[82,96,99],"discriminator":[83,100],"(TWGAN),":[87],"which,":[88],"unlike":[89],"GAN,":[90],"generator":[93,138],"discriminator.":[97],"The":[98,206],"consists":[101],"discriminators":[104],"with":[105,224],"identical":[106],"architecture":[107],"both":[109],"them":[111],"aim":[112],"distinguish":[114],"whether":[115],"samples":[117,203],"are":[118],"real":[120,164],"data":[121,153,165],"or":[122],"fake":[123],"data.":[124],"develop":[126],"theoretical":[127],"analysis":[128],"show":[130,228],"that,":[131],"given":[132],"optimal":[134],"discriminators,":[135],"optimizing":[136],"TWGAN":[140,196],"reduces":[141],"minimizing":[143],"Kullback-Leibler":[145],"(KL)":[146],"divergence":[147],"between":[148],"distribution":[150,162],"generated":[152],"(":[154,166],"<inline-formula":[155,167,215],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[156,168,216],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[157,169,217],"notation=\"LaTeX\">$P_g$</tex-math></inline-formula>":[158],")":[159],"notation=\"LaTeX\">$P_data$</tex-math></inline-formula>":[170],"),":[171],"hence":[172],"addressing":[174],"Extensive":[179],"experiments":[180],"on":[181],"MNIST,":[182,184],"Fashion":[183],"CIFAR-10/100":[185],"STL-10":[187],"datasets":[188],"demonstrate":[189],"that":[190],"competitive":[192],"performance":[193],"in":[197],"generating":[198],"good":[199],"quality":[200],"diverse":[202],"over":[204],"baselines.":[205],"obtained":[207],"highest":[208],"inception":[209],"score":[210],"(IS)":[211],"lowest":[213],"Fr":[214],"notation=\"LaTeX\">$\\acute{e}$</tex-math></inline-formula>":[218],"chet":[219],"Inception":[220],"Distance":[221],"(FID),":[222],"compared":[223],"other":[225],"state-of-the-art":[226],"GANs,":[227],"superiority":[230],"TWGAN.":[233]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}