{"id":"https://openalex.org/W4362565362","doi":"https://doi.org/10.1145/3579895.3579909","title":"Global-Local Feature Alignment Loss for Photorealistic Style Transfer","display_name":"Global-Local Feature Alignment Loss for Photorealistic Style Transfer","publication_year":2022,"publication_date":"2022-12-09","ids":{"openalex":"https://openalex.org/W4362565362","doi":"https://doi.org/10.1145/3579895.3579909"},"language":"en","primary_location":{"id":"doi:10.1145/3579895.3579909","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3579895.3579909","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3579895.3579909","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Networks, Communication and Computing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3579895.3579909","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039978500","display_name":"Yuchao Jing","orcid":"https://orcid.org/0000-0002-4196-4004"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuchao Jing","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0002-3497-1708","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002373133","display_name":"Guoquan Jiang","orcid":"https://orcid.org/0000-0002-8729-0017"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoquan Jiang","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0002-8729-0017","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017764646","display_name":"Zhanqiang Huo","orcid":"https://orcid.org/0000-0001-9243-5009"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanqiang Huo","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0001-9243-5009","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073416762","display_name":"Yijiang Wang","orcid":"https://orcid.org/0000-0001-9347-8844"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijiang Wang","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0001-9347-8844","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024617117","display_name":"Lili Wu","orcid":"https://orcid.org/0000-0003-0680-8716"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Wu","raw_affiliation_strings":["Henan Polytechnic University, China"],"raw_orcid":"https://orcid.org/0000-0003-0680-8716","affiliations":[{"raw_affiliation_string":"Henan Polytechnic University, China","institution_ids":["https://openalex.org/I4210166499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210166499"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23782848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"90","last_page":"95"},"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":0.9987999796867371,"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":0.9987999796867371,"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":0.996399998664856,"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":0.9916999936103821,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7602782249450684},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7292771339416504},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.6865779757499695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5836346745491028},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5673554539680481},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5004439353942871},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49356377124786377},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46268951892852783},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.45028242468833923},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41973668336868286},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4127393364906311},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39741232991218567},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2503160238265991}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7602782249450684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7292771339416504},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6865779757499695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5836346745491028},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5673554539680481},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5004439353942871},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49356377124786377},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46268951892852783},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.45028242468833923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41973668336868286},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4127393364906311},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39741232991218567},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2503160238265991},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3579895.3579909","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3579895.3579909","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3579895.3579909","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Networks, Communication and Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3579895.3579909","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3579895.3579909","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3579895.3579909","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 11th International Conference on Networks, Communication and Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4178204042","display_name":null,"funder_award_id":"19IRTSTHN012","funder_id":"https://openalex.org/F4320322878","funder_display_name":"Henan University"},{"id":"https://openalex.org/G8454719412","display_name":null,"funder_award_id":"62273292","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"},{"id":"https://openalex.org/F4320322878","display_name":"Henan University","ror":"https://ror.org/003xyzq10"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4362565362.pdf","grobid_xml":"https://content.openalex.org/works/W4362565362.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2331128040","https://openalex.org/W2523714292","https://openalex.org/W2550673061","https://openalex.org/W2603777577","https://openalex.org/W2770449959","https://openalex.org/W2788095258","https://openalex.org/W2792410992","https://openalex.org/W2798722152","https://openalex.org/W2805935678","https://openalex.org/W2964168764","https://openalex.org/W3005680577","https://openalex.org/W3092210344","https://openalex.org/W3106758205","https://openalex.org/W3107989310","https://openalex.org/W3108316907","https://openalex.org/W3167478203","https://openalex.org/W3207853298","https://openalex.org/W4221148211","https://openalex.org/W4285077678","https://openalex.org/W4286896453","https://openalex.org/W4312534259","https://openalex.org/W6736014680","https://openalex.org/W6799869042","https://openalex.org/W6810559236"],"related_works":["https://openalex.org/W2069592018","https://openalex.org/W2075740387","https://openalex.org/W2358990940","https://openalex.org/W2093931120","https://openalex.org/W2329812990","https://openalex.org/W2349116365","https://openalex.org/W3021708704","https://openalex.org/W2004231473","https://openalex.org/W2060895226","https://openalex.org/W2151991951"],"abstract_inverted_index":{"The":[0],"problem":[1],"that":[2,124,132,160],"needs":[3],"to":[4,54,70,74,145],"be":[5],"solved":[6],"for":[7],"photorealistic":[8],"style":[9,27,41],"transfer":[10,28],"lies":[11],"in":[12,110],"limiting":[13],"the":[14,20,25,31,48,66,72,83,96,104,125,161],"distortion":[15],"of":[16,19,85,98,103],"texture":[17],"details":[18],"generated":[21,90],"image":[22,106,109],"based":[23,64,91],"on":[24,65,92],"typical":[26],"network.":[29],"Although":[30],"existing":[32],"methods":[33],"achieve":[34,146,166],"better":[35],"stylization":[36,148,168],"results,":[37],"they":[38,44],"lack":[39],"sufficient":[40],"information":[42,79,120,134],"because":[43],"do":[45],"not":[46],"consider":[47],"feature":[49,152],"map":[50],"comprehensively":[51],"enough,":[52],"leading":[53],"exposure":[55],"or":[56],"artifacts.":[57],"This":[58,113],"article":[59,138],"proposes":[60,139],"a":[61,140],"loss":[62],"function":[63],"contrast":[67],"learning":[68],"method":[69,163],"constrain":[71],"network":[73,126,144],"extract":[75],"local":[76,117],"and":[77,95,107,118,129,131,169],"global":[78,119],"effectively.":[80],"It":[81],"ensures":[82,114],"consistency":[84,97,115],"distribution":[86],"among":[87],"regional":[88],"blocks":[89],"anchor":[93,101],"points":[94,102],"comparison":[99],"between":[100,116],"resulting":[105],"content":[108],"their":[111],"neighborhood.":[112],"comparisons.":[121],"To":[122],"ensure":[123],"is":[127,135],"simple":[128],"effective":[130],"enough":[133],"extracted,":[136],"this":[137],"linear":[141],"covariance":[142],"transformation":[143],"faithful":[147],"by":[149],"effectively":[150],"fusing":[151],"first-order":[153],"statistics":[154],"with":[155],"second-order":[156],"statistics.":[157],"Experiments":[158],"show":[159],"proposed":[162],"can":[164],"faithfully":[165],"realistic":[167],"satisfying":[170],"visual":[171],"effects.":[172]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}