{"id":"https://openalex.org/W4312477183","doi":"https://doi.org/10.1109/tpami.2022.3231649","title":"ScoreMix: A Scalable Augmentation Strategy for Training GANs With Limited Data","display_name":"ScoreMix: A Scalable Augmentation Strategy for Training GANs With Limited Data","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312477183","doi":"https://doi.org/10.1109/tpami.2022.3231649","pmid":"https://pubmed.ncbi.nlm.nih.gov/37015400"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3231649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3231649","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5051771665","display_name":"Jie Cao","orcid":"https://orcid.org/0000-0001-6368-4495"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Cao","raw_affiliation_strings":["CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064812067","display_name":"Mandi Luo","orcid":"https://orcid.org/0000-0001-8298-3220"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mandi Luo","raw_affiliation_strings":["CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060684352","display_name":"Junchi Yu","orcid":"https://orcid.org/0000-0003-4118-3248"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junchi Yu","raw_affiliation_strings":["CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418319","display_name":"Ming\u2013Hsuan Yang","orcid":"https://orcid.org/0000-0003-4848-2304"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]},{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Ming-Hsuan Yang","raw_affiliation_strings":["University of California, Merced, USA","Yonsei University, South Korea","Google"],"affiliations":[{"raw_affiliation_string":"University of California, Merced, USA","institution_ids":["https://openalex.org/I156087764"]},{"raw_affiliation_string":"Yonsei University, South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112749024","display_name":"Ran He","orcid":"https://orcid.org/0000-0002-3807-991X"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran He","raw_affiliation_strings":["CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"CRIPAC &amp; NLPR, Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5051771665"],"corresponding_institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.6301,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.85182401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"45","issue":"7","first_page":"1","last_page":"16"},"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":0.9983999729156494,"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":0.9983999729156494,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9742000102996826,"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/computer-science","display_name":"Computer science","score":0.773833692073822},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6458542346954346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6273142099380493},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5755959153175354},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5596585869789124},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44066035747528076},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33581674098968506},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09447246789932251}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.773833692073822},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6458542346954346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6273142099380493},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5755959153175354},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5596585869789124},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44066035747528076},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33581674098968506},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09447246789932251},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3231649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3231649","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37015400","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37015400","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":113,"referenced_works":["https://openalex.org/W1505878979","https://openalex.org/W1834627138","https://openalex.org/W1873595945","https://openalex.org/W2013035813","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2137844145","https://openalex.org/W2151239833","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2545656684","https://openalex.org/W2563705555","https://openalex.org/W2604721644","https://openalex.org/W2746314669","https://openalex.org/W2761299546","https://openalex.org/W2765407302","https://openalex.org/W2792263949","https://openalex.org/W2801495938","https://openalex.org/W2891021639","https://openalex.org/W2921320475","https://openalex.org/W2949736877","https://openalex.org/W2951751045","https://openalex.org/W2952716587","https://openalex.org/W2959300817","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2963306805","https://openalex.org/W2963373786","https://openalex.org/W2963704386","https://openalex.org/W2963873275","https://openalex.org/W2964050021","https://openalex.org/W2964125246","https://openalex.org/W2978426779","https://openalex.org/W2982041717","https://openalex.org/W2989149111","https://openalex.org/W2989855043","https://openalex.org/W2990452356","https://openalex.org/W2992308087","https://openalex.org/W2994088087","https://openalex.org/W2996108195","https://openalex.org/W2996690341","https://openalex.org/W2997564604","https://openalex.org/W3001197829","https://openalex.org/W3004970274","https://openalex.org/W3005680577","https://openalex.org/W3033085318","https://openalex.org/W3033721867","https://openalex.org/W3034600949","https://openalex.org/W3034720584","https://openalex.org/W3035125609","https://openalex.org/W3035574324","https://openalex.org/W3035682985","https://openalex.org/W3036167779","https://openalex.org/W3080580366","https://openalex.org/W3086731747","https://openalex.org/W3090114880","https://openalex.org/W3099088591","https://openalex.org/W3105013723","https://openalex.org/W3108316907","https://openalex.org/W3110257065","https://openalex.org/W3112437058","https://openalex.org/W3119439276","https://openalex.org/W3120254195","https://openalex.org/W3125645205","https://openalex.org/W3167204053","https://openalex.org/W3171615848","https://openalex.org/W3174417809","https://openalex.org/W4288088427","https://openalex.org/W4294643831","https://openalex.org/W4295521014","https://openalex.org/W4300439197","https://openalex.org/W4301206121","https://openalex.org/W4320013936","https://openalex.org/W6639201957","https://openalex.org/W6680211044","https://openalex.org/W6682208247","https://openalex.org/W6684191040","https://openalex.org/W6718379498","https://openalex.org/W6729110096","https://openalex.org/W6735249503","https://openalex.org/W6735913928","https://openalex.org/W6743428213","https://openalex.org/W6743716298","https://openalex.org/W6745136726","https://openalex.org/W6745560452","https://openalex.org/W6746090280","https://openalex.org/W6749927861","https://openalex.org/W6755312952","https://openalex.org/W6760606919","https://openalex.org/W6762334975","https://openalex.org/W6762913911","https://openalex.org/W6765775151","https://openalex.org/W6765779288","https://openalex.org/W6769148693","https://openalex.org/W6769201011","https://openalex.org/W6770979763","https://openalex.org/W6771630921","https://openalex.org/W6772167297","https://openalex.org/W6773005947","https://openalex.org/W6774314701","https://openalex.org/W6778946027","https://openalex.org/W6778963470","https://openalex.org/W6779092321","https://openalex.org/W6779093361","https://openalex.org/W6779447676","https://openalex.org/W6779487818","https://openalex.org/W6779669310","https://openalex.org/W6779823529","https://openalex.org/W6780507278","https://openalex.org/W6783961830","https://openalex.org/W6784078097","https://openalex.org/W6786375611"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W2389214306","https://openalex.org/W3216976533","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W2551249631"],"abstract_inverted_index":{"Generative":[0],"Adversarial":[1],"Networks":[2],"(GANs)":[3],"typically":[4],"suffer":[5],"from":[6],"overfitting":[7,158],"when":[8],"limited":[9],"training":[10],"data":[11,50,83,101,154],"is":[12,30],"available.":[13],"To":[14,103],"facilitate":[15],"GAN":[16,168,180],"training,":[17],"current":[18],"methods":[19,34],"propose":[20],"to":[21,35,37,99,142],"use":[22],"data-specific":[23],"augmentation":[24,51],"techniques.":[25],"Despite":[26],"the":[27,64,68,74,79,82,86,89,95,100,105,124,135,138,143,151,157,184],"effectiveness,":[28],"it":[29,161],"difficult":[31],"for":[32,53],"these":[33],"scale":[36],"practical":[38],"applications.":[39],"In":[40],"this":[41],"article,":[42],"we":[43,72,107,122],"present":[44],"ScoreMix,":[45],"a":[46,109],"novel":[47],"and":[48,155],"scalable":[49],"approach":[52],"various":[54],"image":[55,119],"synthesis":[56,120],"tasks.":[57],"We":[58,131],"first":[59],"produce":[60],"augmented":[61,75,96],"samples":[62,76,97],"using":[63,128],"convex":[65],"combinations":[66],"of":[67,81,88,137,153],"real":[69],"samples.":[70],"Then,":[71],"optimize":[73],"by":[77],"minimizing":[78],"norms":[80],"scores,":[84,106],"i.e.,":[85],"gradients":[87],"log-density":[90],"functions.":[91],"This":[92],"procedure":[93],"enforces":[94],"close":[98],"manifold.":[102],"estimate":[104],"train":[108,123],"deep":[110],"estimation":[111,126],"network":[112,127,144],"with":[113,170,183],"multi-scale":[114],"score":[115,125],"matching.":[116],"For":[117],"different":[118,129],"tasks,":[121],"data.":[130],"do":[132],"not":[133],"require":[134],"tuning":[136],"hyperparameters":[139],"or":[140],"modifications":[141],"architecture.":[145],"The":[146],"ScoreMix":[147,185],"method":[148,186],"effectively":[149],"increases":[150],"diversity":[152],"reduces":[156],"problem.":[159],"Moreover,":[160],"can":[162],"be":[163],"easily":[164],"incorporated":[165],"into":[166],"existing":[167],"models":[169,181],"minor":[171],"modifications.":[172],"Experimental":[173],"results":[174],"on":[175],"numerous":[176],"tasks":[177],"demonstrate":[178],"that":[179],"equipped":[182],"achieve":[187],"significant":[188],"improvements.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
