{"id":"https://openalex.org/W4390874576","doi":"https://doi.org/10.1109/iccv51070.2023.01585","title":"UGC: Unified GAN Compression for Efficient Image-to-Image Translation","display_name":"UGC: Unified GAN Compression for Efficient Image-to-Image Translation","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390874576","doi":"https://doi.org/10.1109/iccv51070.2023.01585"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51070.2023.01585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","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/A5013516109","display_name":"Yuxi Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yuxi Ren","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440114","display_name":"Jie Wu","orcid":"https://orcid.org/0000-0002-7211-2816"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Wu","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055082237","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-5409-7480"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029760435","display_name":"Manlin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manlin Zhang","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101051966","display_name":"Xuefeng Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuefeng Xiao","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720517","display_name":"Qian He","orcid":"https://orcid.org/0000-0003-4346-9899"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian He","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100417876","display_name":"Rui Wang","orcid":"https://orcid.org/0009-0001-1318-5038"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Wang","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100521432","display_name":"Min Zheng","orcid":"https://orcid.org/0000-0002-2404-5006"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Min Zheng","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102247816","display_name":"Xin Pan","orcid":"https://orcid.org/0009-0005-7997-7643"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin Pan","raw_affiliation_strings":["ByteDance Inc"],"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5013516109"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7198,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73710728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"17235","last_page":"17245"},"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":0.9968000054359436,"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":0.9968000054359436,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9871000051498413,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9869999885559082,"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/computer-science","display_name":"Computer science","score":0.7951103448867798},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5828328728675842},{"id":"https://openalex.org/keywords/image-translation","display_name":"Image translation","score":0.5738330483436584},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5329288840293884},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5195103883743286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4972870647907257},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.43449270725250244},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4173429012298584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7951103448867798},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5828328728675842},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.5738330483436584},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5329288840293884},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5195103883743286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4972870647907257},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.43449270725250244},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4173429012298584},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv51070.2023.01585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2093848332","https://openalex.org/W2103559027","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2331128040","https://openalex.org/W2340897893","https://openalex.org/W2405756170","https://openalex.org/W2559655401","https://openalex.org/W2785678896","https://openalex.org/W2798729263","https://openalex.org/W2804078698","https://openalex.org/W2952716587","https://openalex.org/W2953096069","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2962974533","https://openalex.org/W2963073614","https://openalex.org/W2963684088","https://openalex.org/W2963767194","https://openalex.org/W2963800363","https://openalex.org/W2983484869","https://openalex.org/W2989221291","https://openalex.org/W3001197829","https://openalex.org/W3033085318","https://openalex.org/W3034720584","https://openalex.org/W3035147638","https://openalex.org/W3035204081","https://openalex.org/W3035574324","https://openalex.org/W3035593893","https://openalex.org/W3099088591","https://openalex.org/W3100565014","https://openalex.org/W3109946440","https://openalex.org/W3167305632","https://openalex.org/W3168622113","https://openalex.org/W3171615848","https://openalex.org/W3173855227","https://openalex.org/W3174417809","https://openalex.org/W3174480022","https://openalex.org/W3177640626","https://openalex.org/W3195362412","https://openalex.org/W3209253923","https://openalex.org/W4221167590","https://openalex.org/W4225603038","https://openalex.org/W4288020585","https://openalex.org/W4301206121","https://openalex.org/W4312423208","https://openalex.org/W4312440098","https://openalex.org/W4312770623","https://openalex.org/W4312984277","https://openalex.org/W6685352114","https://openalex.org/W6713645886","https://openalex.org/W6748582592","https://openalex.org/W6752378368","https://openalex.org/W6755312952","https://openalex.org/W6765779288","https://openalex.org/W6770578729","https://openalex.org/W6773005947","https://openalex.org/W6779092321","https://openalex.org/W6779093361","https://openalex.org/W6779487836","https://openalex.org/W6779669310","https://openalex.org/W6780507278","https://openalex.org/W6785083360","https://openalex.org/W6796695833","https://openalex.org/W6803232112"],"related_works":["https://openalex.org/W4288069866","https://openalex.org/W3166978923","https://openalex.org/W4389232935","https://openalex.org/W2986947168","https://openalex.org/W2904276469","https://openalex.org/W3109545856","https://openalex.org/W2971888217","https://openalex.org/W2798873573","https://openalex.org/W4213477128","https://openalex.org/W3101578490"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2],"witnessed":[3],"the":[4,16,58,81,149],"prevailing":[5],"progress":[6],"of":[7,18,60,83],"Generative":[8],"Adversarial":[9],"Networks":[10],"(GANs)":[11],"in":[12],"image-to-image":[13],"translation.":[14],"However,":[15],"success":[17],"these":[19],"GAN":[20,33,70],"models":[21,125],"hinges":[22],"on":[23,141],"ponderous":[24],"computational":[25],"costs":[26],"and":[27,85,95,114],"labor-expensive":[28],"training":[29,54],"data.":[30],"Current":[31],"efficient":[32],"learning":[34,51,67,107],"techniques":[35],"often":[36],"fall":[37],"into":[38],"two":[39],"orthogonal":[40],"aspects:":[41],"i)":[42],"model":[43,151],"slimming":[44],"via":[45],"reduced":[46],"calculation":[47],"costs;":[48],"ii)":[49],"data/label-efficient":[50],"with":[52,73,127,143,152],"fewer":[53],"data/labels.":[55],"To":[56],"combine":[57],"best":[59],"both":[61],"worlds,":[62],"we":[63],"propose":[64],"a":[65,74,104],"new":[66],"paradigm,":[68],"Unified":[69],"Compression":[71],"(UGC),":[72],"unified":[75],"optimization":[76],"objective":[77],"to":[78,109],"seamlessly":[79],"prompt":[80],"synergy":[82],"model-efficient":[84],"label-efficient":[86],"learning.":[87],"UGC":[88,121,132],"sets":[89],"up":[90],"semi-supervised-driven":[91],"network":[92],"architecture":[93],"search":[94],"adaptive":[96],"online":[97],"semi-supervised":[98],"distillation":[99],"stages":[100],"sequentially,":[101],"which":[102,146],"formulates":[103],"heterogeneous":[105],"mutual":[106],"scheme":[108],"obtain":[110],"an":[111],"architecture-flexible,":[112],"label-efficient,":[113],"performance-excellent":[115],"model.":[116],"Extensive":[117],"experiments":[118],"demonstrate":[119],"that":[120,133],"obtains":[122],"state-of-the-art":[123],"lightweight":[124],"even":[126,147],"less":[128],"than":[129],"50%":[130],"labels.":[131],"compresses":[134],"40\u00d7":[135],"MACs":[136],"can":[137],"achieve":[138],"21.43":[139],"FID":[140],"edges\u2192shoes":[142],"25%":[144],"labels,":[145],"outperforms":[148],"original":[150],"100%":[153],"labels":[154],"by":[155],"2.75":[156],"FID.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}