{"id":"https://openalex.org/W4307771767","doi":"https://doi.org/10.1109/tip.2022.3215899","title":"CLAST: Contrastive Learning for Arbitrary Style Transfer","display_name":"CLAST: Contrastive Learning for Arbitrary Style Transfer","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4307771767","doi":"https://doi.org/10.1109/tip.2022.3215899","pmid":"https://pubmed.ncbi.nlm.nih.gov/36282821"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3215899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3215899","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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/A5100772594","display_name":"Xinhao Wang","orcid":"https://orcid.org/0000-0002-0366-7543"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinhao Wang","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0366-7543","affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429487","display_name":"Wenjing Wang","orcid":"https://orcid.org/0000-0003-3951-3877"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Wang","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3951-3877","affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736164","display_name":"Shuai Yang","orcid":"https://orcid.org/0000-0002-5576-8629"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shuai Yang","raw_affiliation_strings":["S-Lab for Advanced Intelligence, Nanyang Technological University, Jurong West, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-5576-8629","affiliations":[{"raw_affiliation_string":"S-Lab for Advanced Intelligence, Nanyang Technological University, Jurong West, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100761525","display_name":"Jiaying Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaying Liu","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0468-9576","affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100772594"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":2.5377,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.90935283,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"31","issue":null,"first_page":"6761","last_page":"6772"},"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":0.9962999820709229,"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":0.9962999820709229,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9839000105857849,"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":0.9456999897956848,"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/stylized-fact","display_name":"Stylized fact","score":0.6962911486625671},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6761157512664795},{"id":"https://openalex.org/keywords/style","display_name":"Style (visual arts)","score":0.6634945869445801},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.614115834236145},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5454431772232056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49285435676574707},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.42750829458236694},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4239041805267334},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1420241892337799}],"concepts":[{"id":"https://openalex.org/C38935604","wikidata":"https://www.wikidata.org/wiki/Q4330363","display_name":"Stylized fact","level":2,"score":0.6962911486625671},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6761157512664795},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.6634945869445801},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.614115834236145},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5454431772232056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49285435676574707},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.42750829458236694},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4239041805267334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1420241892337799},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2022.3215899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3215899","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:36282821","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36282821","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1102186166","display_name":null,"funder_award_id":"62172020","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1999360130","https://openalex.org/W2078718577","https://openalex.org/W2078790577","https://openalex.org/W2116013899","https://openalex.org/W2125027853","https://openalex.org/W2125879936","https://openalex.org/W2127006916","https://openalex.org/W2138621090","https://openalex.org/W2275363859","https://openalex.org/W2292976057","https://openalex.org/W2331128040","https://openalex.org/W2339754110","https://openalex.org/W2344328033","https://openalex.org/W2475287302","https://openalex.org/W2572730214","https://openalex.org/W2603777577","https://openalex.org/W2798520250","https://openalex.org/W2798722152","https://openalex.org/W2798729263","https://openalex.org/W2842511635","https://openalex.org/W2884041121","https://openalex.org/W2962793481","https://openalex.org/W2963683323","https://openalex.org/W2966141073","https://openalex.org/W2969803502","https://openalex.org/W2969810168","https://openalex.org/W2970027214","https://openalex.org/W2986779468","https://openalex.org/W2989045104","https://openalex.org/W2998432172","https://openalex.org/W3034580487","https://openalex.org/W3035026630","https://openalex.org/W3035060554","https://openalex.org/W3035524453","https://openalex.org/W3066471605","https://openalex.org/W3087124270","https://openalex.org/W3088751363","https://openalex.org/W3093370337","https://openalex.org/W3102542372","https://openalex.org/W3108316907","https://openalex.org/W3128661784","https://openalex.org/W3128990302","https://openalex.org/W3169978599","https://openalex.org/W3171007011","https://openalex.org/W3173752239","https://openalex.org/W3174883353","https://openalex.org/W3176395558","https://openalex.org/W3177457352","https://openalex.org/W3179365255","https://openalex.org/W3202767484","https://openalex.org/W3204777666","https://openalex.org/W4226144843","https://openalex.org/W4294068600","https://openalex.org/W4297808394","https://openalex.org/W4298135604","https://openalex.org/W6637373629","https://openalex.org/W6731043416","https://openalex.org/W6738438352","https://openalex.org/W6774314701","https://openalex.org/W6779326418","https://openalex.org/W6786142540"],"related_works":["https://openalex.org/W2132789450","https://openalex.org/W2481841423","https://openalex.org/W2181566835","https://openalex.org/W3160062981","https://openalex.org/W217193869","https://openalex.org/W3036201115","https://openalex.org/W2572930635","https://openalex.org/W1974191481","https://openalex.org/W2803075872","https://openalex.org/W2783913440"],"abstract_inverted_index":{"Arbitrary":[0],"style":[1,7,11,29,62,77,84,96,109,119,134,147],"transfer":[2,135,148],"aims":[3],"at":[4,31],"migrating":[5],"the":[6,32,65,72,122],"of":[8,47,93],"a":[9,14,112,132],"reference":[10],"painting":[12],"to":[13,23,57,67,70,117,145],"target":[15],"content":[16,26,42,74,94,115],"image.":[17],"Existing":[18],"methods":[19],"find":[20],"it":[21],"challenging":[22],"achieve":[24],"good":[25],"fidelity":[27],"and":[28,43,50,75,95,100,111,126,140,159],"migration":[30],"same":[33],"time.":[34],"Moreover,":[35],"they":[36],"all":[37],"rely":[38],"on":[39,79],"manually":[40],"defined":[41],"style,":[44],"which":[45,137],"is":[46,97,138],"limited":[48],"universality":[49],"robustness.":[51],"In":[52,102],"this":[53],"paper,":[54],"we":[55,104,130],"propose":[56,106],"introduce":[58],"contrastive":[59,81,108,114,124],"learning":[60],"into":[61],"transfer,":[63],"instructing":[64],"network":[66],"automatically":[68],"learn":[69],"model":[71],"structural":[73],"artistic":[76],"based":[78],"natural":[80],"relationships":[82],"in":[83],"transfer.":[85,120],"Compared":[86],"with":[87,163],"existing":[88],"methods,":[89],"our":[90,154],"learned":[91],"modeling":[92],"more":[98],"robust":[99],"universal.":[101],"addition,":[103],"further":[105],"instance-wise":[107],"losses":[110,125],"patch-wise":[113],"loss":[116],"guide":[118],"Combining":[121],"proposed":[123],"two":[127],"self-reconstruction":[128],"strategies,":[129],"develop":[131],"new":[133],"framework,":[136],"pluggable":[139],"can":[141],"be":[142],"flexibly":[143],"applied":[144],"various":[146],"modules.":[149],"Experimental":[150],"results":[151],"demonstrate":[152],"that":[153],"method":[155],"has":[156],"strong":[157],"flexibility":[158],"synthesizes":[160],"stylized":[161],"images":[162],"higher":[164],"quality.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-02T09:04:35.204637","created_date":"2025-10-10T00:00:00"}
