{"id":"https://openalex.org/W7160257958","doi":"https://doi.org/10.1109/wacv61042.2026.00110","title":"Diverse Sketch Colorization with Content-Enhanced Style Representation and Recolorization Distillation","display_name":"Diverse Sketch Colorization with Content-Enhanced Style Representation and Recolorization Distillation","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160257958","doi":"https://doi.org/10.1109/wacv61042.2026.00110"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","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/A5048991627","display_name":"Shuangming Mao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuangming Mao","raw_affiliation_strings":["Independent Researcher,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Independent Researcher,Shanghai,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135291680","display_name":"Haixiang Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I198357462","display_name":"Changsha University","ror":"https://ror.org/011d8sm39","country_code":"CN","type":"education","lineage":["https://openalex.org/I198357462"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haixiang Zhu","raw_affiliation_strings":["Independent Researcher,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Independent Researcher,Changsha,China","institution_ids":["https://openalex.org/I198357462"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68375302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1064","last_page":"1073"},"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":0.9796000123023987,"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":0.9796000123023987,"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/T11448","display_name":"Face recognition and analysis","score":0.006200000178068876,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.0015999999595806003,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7932999730110168},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6525999903678894},{"id":"https://openalex.org/keywords/style","display_name":"Style (visual arts)","score":0.46700000762939453},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.329800009727478},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3264000117778778}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7932999730110168},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6525999903678894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6327999830245972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5735999941825867},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.46700000762939453},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32190001010894775},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27639999985694885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2623000144958496},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2326925005","https://openalex.org/W2560481159","https://openalex.org/W2902318149","https://openalex.org/W2962974533","https://openalex.org/W2963073614","https://openalex.org/W2963306805","https://openalex.org/W2963561004","https://openalex.org/W2963890275","https://openalex.org/W2981824749","https://openalex.org/W2987285147","https://openalex.org/W2990269423","https://openalex.org/W3034600949","https://openalex.org/W3034832575","https://openalex.org/W3035124078","https://openalex.org/W3035574324","https://openalex.org/W3115218903","https://openalex.org/W3118910650","https://openalex.org/W3145450063","https://openalex.org/W3174868683","https://openalex.org/W3177221875","https://openalex.org/W3180355996","https://openalex.org/W3180675665","https://openalex.org/W3181462058","https://openalex.org/W3212516020","https://openalex.org/W4226077360","https://openalex.org/W4283816659","https://openalex.org/W4292828959","https://openalex.org/W4311802540","https://openalex.org/W4312821384","https://openalex.org/W4312911498","https://openalex.org/W4313021454","https://openalex.org/W4319300995","https://openalex.org/W4385527149","https://openalex.org/W4385537492","https://openalex.org/W4386071584","https://openalex.org/W4386075870","https://openalex.org/W4386076154","https://openalex.org/W4390873054","https://openalex.org/W4393148714"],"related_works":[],"abstract_inverted_index":{"Sketch":[0],"colorization":[1,148,171],"is":[2],"highly":[3],"demanded":[4],"in":[5,36,57,88,121,189],"the":[6,52,59,106,122,128,142,147,170,176],"field":[7],"of":[8,55,69,108,178],"art,":[9],"as":[10,40,146],"it":[11,32],"offers":[12],"a":[13,30,42,134],"valuable":[14],"tool":[15],"for":[16,84,159,169],"artists,":[17],"designers,":[18],"and":[19,25,67,104,110,118,192],"illustrators":[20],"to":[21,51,76,165],"explore":[22],"novel":[23],"possibilities":[24],"express":[26],"their":[27],"creativity.":[28],"Given":[29],"sketch,":[31,161],"can":[33,81,154],"be":[34],"colorized":[35,61,190],"various":[37],"styles,":[38],"such":[39],"rendering":[41],"facial":[43],"sketch":[44],"with":[45],"different":[46],"hair":[47],"colors.":[48,197],"However,":[49],"due":[50],"inherent":[53],"scarcity":[54],"information":[56,87,101],"sketches,":[58],"resulting":[60],"images":[62,120],"often":[63],"exhibit":[64],"noticeable":[65],"artifacts":[66,188],"lack":[68],"diversity.":[70],"In":[71,150],"this":[72,151],"paper,":[73],"we":[74,131,153],"aim":[75],"generate":[77],"informative-style":[78],"representations":[79],"that":[80,183],"effectively":[82,186],"compensate":[83],"missing":[85],"content":[86,109],"sketches":[89,117],"while":[90],"enabling":[91],"diverse":[92],"generations.":[93],"We":[94],"improve":[95,127],"style":[96,100,111,144],"granularity":[97],"by":[98,112],"extracting":[99],"from":[102],"CLIP,":[103],"achieve":[105],"disentanglement":[107],"establishing":[113],"semantic":[114,129,179],"correspondence":[115],"between":[116],"color":[119],"CLIP":[123],"space.":[124],"To":[125],"further":[126],"accuracy,":[130],"simultaneously":[132],"train":[133],"recolorization":[135,139],"model":[136,140],"end-to-end.":[137],"The":[138],"shares":[141],"same":[143],"space":[145],"model.":[149],"way,":[152],"construct":[155],"multiple":[156],"pseudo-sketch-image":[157],"pairs":[158],"each":[160],"which":[162],"are":[163],"used":[164],"provide":[166],"pixel-level":[167],"supervision":[168],"model,":[172],"thus":[173],"significantly":[174],"facilitating":[175],"learning":[177],"correspondence.":[180],"Experiments":[181],"demonstrate":[182],"our":[184],"method":[185],"mitigates":[187],"results":[191],"produces":[193],"more":[194],"semantically":[195],"rich":[196]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}
