{"id":"https://openalex.org/W4200565423","doi":"https://doi.org/10.1145/3476124.3488634","title":"Class Balanced Sampling for the Training in GANs","display_name":"Class Balanced Sampling for the Training in GANs","publication_year":2021,"publication_date":"2021-12-11","ids":{"openalex":"https://openalex.org/W4200565423","doi":"https://doi.org/10.1145/3476124.3488634"},"language":"en","primary_location":{"id":"doi:10.1145/3476124.3488634","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3476124.3488634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2021 Posters","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/A5100705921","display_name":"Sanghun Kim","orcid":"https://orcid.org/0000-0002-1423-6116"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sanghun Kim","raw_affiliation_strings":["KHU, South Korea"],"affiliations":[{"raw_affiliation_string":"KHU, South Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101472509","display_name":"Seungkyu Lee","orcid":"https://orcid.org/0000-0002-9721-4093"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seungkyu Lee","raw_affiliation_strings":["KHU, South Korea"],"affiliations":[{"raw_affiliation_string":"KHU, South Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100705921"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.19423809,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9923999905586243,"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/selection","display_name":"Selection (genetic algorithm)","score":0.763805091381073},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.7342296838760376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6965224146842957},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6619811058044434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5882288813591003},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.537112295627594},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5309975147247314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5015640258789062},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4525472819805145},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.42234665155410767},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3271726965904236},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2273259460926056}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.763805091381073},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.7342296838760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6965224146842957},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6619811058044434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5882288813591003},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.537112295627594},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5309975147247314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5015640258789062},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4525472819805145},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.42234665155410767},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3271726965904236},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2273259460926056},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3476124.3488634","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3476124.3488634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2021 Posters","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":0,"referenced_works":[],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Recently":[0],"Top-k":[1,71],"fake":[2],"sample":[3,51,57],"selection":[4,52],"has":[5],"been":[6],"introduced":[7],"to":[8,69],"provide":[9],"better":[10],"gradients":[11],"for":[12],"training":[13],"Generative":[14],"Adversarial":[15],"Networks.":[16],"Since":[17],"the":[18,39],"method":[19,60],"does":[20],"not":[21],"guarantee":[22],"class":[23,29,46,55],"balance":[24],"of":[25],"selected":[26],"samples":[27],"in":[28,38],"conditional":[30],"GANs,":[31],"certain":[32],"classes":[33],"can":[34],"be":[35],"completely":[36],"ignored":[37],"training.":[40],"In":[41],"this":[42],"work,":[43],"we":[44],"propose":[45],"standardized":[47],"critic":[48],"score":[49,64,67],"based":[50],"which":[53],"enables":[54],"balanced":[56],"selection.":[58,72],"Our":[59],"achieves":[61],"improved":[62],"FID":[63],"and":[65],"Intra-FID":[66],"compared":[68],"prior":[70]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
