{"id":"https://openalex.org/W3091102562","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207095","title":"Redistributing and Re-Stylizing Features for Training a Fast Photorealistic Stylizer","display_name":"Redistributing and Re-Stylizing Features for Training a Fast Photorealistic Stylizer","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3091102562","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207095","mag":"3091102562"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5048629905","display_name":"Chunpeng Wu","orcid":"https://orcid.org/0000-0002-3970-8570"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chunpeng Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010881036","display_name":"Bin Ni","orcid":"https://orcid.org/0000-0002-1684-6372"},"institutions":[{"id":"https://openalex.org/I4210145189","display_name":"Quantix (United States)","ror":"https://ror.org/04vpnsj12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145189"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Ni","raw_affiliation_strings":["QUANTIL Inc., Santa Clara, CA, USA"],"affiliations":[{"raw_affiliation_string":"QUANTIL Inc., Santa Clara, CA, USA","institution_ids":["https://openalex.org/I4210145189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100429377","display_name":"Hai Li","orcid":"https://orcid.org/0000-0001-8504-5811"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hai Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048629905"],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.10711165,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9994999766349792,"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":0.9994999766349792,"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":0.9962000250816345,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.8089789152145386},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7255846261978149},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4905681014060974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.465913325548172},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4368557035923004},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3220352530479431},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2993953824043274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8089789152145386},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7255846261978149},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4905681014060974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.465913325548172},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4368557035923004},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3220352530479431},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2993953824043274},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1594772103","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1924619199","https://openalex.org/W1993120651","https://openalex.org/W1999360130","https://openalex.org/W2133665775","https://openalex.org/W2275363859","https://openalex.org/W2284050935","https://openalex.org/W2295130376","https://openalex.org/W2331128040","https://openalex.org/W2339754110","https://openalex.org/W2475287302","https://openalex.org/W2520715860","https://openalex.org/W2545656684","https://openalex.org/W2548275288","https://openalex.org/W2564755245","https://openalex.org/W2572559801","https://openalex.org/W2585235684","https://openalex.org/W2603777577","https://openalex.org/W2604721644","https://openalex.org/W2604737827","https://openalex.org/W2611605760","https://openalex.org/W2612034718","https://openalex.org/W2612696203","https://openalex.org/W2617602381","https://openalex.org/W2619736762","https://openalex.org/W2733509922","https://openalex.org/W2740546229","https://openalex.org/W2892269335","https://openalex.org/W2893749619","https://openalex.org/W2949848065","https://openalex.org/W2950776302","https://openalex.org/W2952716587","https://openalex.org/W2962750014","https://openalex.org/W2962760235","https://openalex.org/W2962770929","https://openalex.org/W2962772087","https://openalex.org/W2962777745","https://openalex.org/W2962835968","https://openalex.org/W2963373786","https://openalex.org/W2963525668","https://openalex.org/W2963683323","https://openalex.org/W2963685250","https://openalex.org/W2963836885","https://openalex.org/W2963890275","https://openalex.org/W2963920537","https://openalex.org/W2963981733","https://openalex.org/W2964121744","https://openalex.org/W2964309429","https://openalex.org/W2968424372","https://openalex.org/W2984648456","https://openalex.org/W3105371893","https://openalex.org/W4294643831","https://openalex.org/W4297749385","https://openalex.org/W4298135604","https://openalex.org/W4301206121","https://openalex.org/W6631190155","https://openalex.org/W6635456918","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6640174519","https://openalex.org/W6695676441","https://openalex.org/W6697028695","https://openalex.org/W6702130928","https://openalex.org/W6703724764","https://openalex.org/W6718379498","https://openalex.org/W6729110096","https://openalex.org/W6729482032","https://openalex.org/W6731043416","https://openalex.org/W6733155073","https://openalex.org/W6735957806","https://openalex.org/W6737806620","https://openalex.org/W6737822200","https://openalex.org/W6738438352","https://openalex.org/W6738676896","https://openalex.org/W6745560452","https://openalex.org/W6748038043","https://openalex.org/W6748953158","https://openalex.org/W6750298367","https://openalex.org/W6754923448","https://openalex.org/W6755312952","https://openalex.org/W6765779288"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2019977573","https://openalex.org/W2149980199","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Style":[0],"transfer":[1,13,36,59,70],"studies":[2,199],"can":[3],"be":[4],"categorized":[5],"into":[6,121],"two":[7,97],"types-artistic":[8],"and":[9,30,46,84,102,194,209],"photorealistic.":[10],"The":[11,92,146],"high-speed":[12],"has":[14],"been":[15],"well-studied":[16],"for":[17,23],"artistic":[18],"styles":[19],"but":[20],"remains":[21],"challenging":[22],"photorealistic":[24,34],"styles.":[25],"To":[26],"guarantee":[27],"semantic":[28,144],"accuracy":[29],"style":[31,35,90,119],"faithfulness,":[32],"prior":[33],"techniques":[37],"often":[38],"rely":[39],"on":[40,152,191],"intensive":[41],"feature":[42,100,136],"matching,":[43],"hierarchical":[44],"stylization,":[45],"complex":[47,76],"auxiliary":[48,77],"smoothing.":[49,78],"Such":[50],"high":[51],"design":[52,80],"complexity":[53],"severely":[54],"limits":[55],"the":[56,69,154,201,212],"space":[57],"of":[58,96,107,163,204,214],"speed":[60],"improvement.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"propose":[66],"to":[67,88,115,142,159,172,211],"accelerate":[68],"through":[71],"a":[72,81],"single-level":[73],"stylization":[74],"without":[75],"We":[79],"two-stage":[82],"\"stylization":[83],"re-stylization\"":[85],"training":[86],"pipeline":[87],"enhance":[89],"faithfulness.":[91],"stylization/re-stylization":[93],"stage":[94],"consists":[95],"core":[98],"steps:":[99],"aggregation":[101],"redistribution.":[103],"A":[104,128],"new":[105],"type":[106],"layers,":[108,112],"Feature":[109],"Aggregation":[110],"(FA)":[111],"is":[113,139],"proposed":[114,206],"gradually":[116],"aggregate":[117],"multi-scale":[118],"features":[120,123,156],"content":[122,165],"at":[124,135,179],"each":[125],"spatial":[126,161],"location.":[127],"Spatially":[129],"coherent":[130],"Content-style":[131],"Preserving":[132],"(SCP)":[133],"loss":[134,148,208],"map":[137],"level":[138],"then":[140],"used":[141],"preserve":[143],"accuracy.":[145],"SCP":[147,207],"provides":[149],"effective":[150],"guidance":[151],"redistributing":[153],"aggregated":[155],"between":[157],"locations":[158],"enforce":[160],"coherence":[162],"style-sensitive":[164],"semantic.":[166],"Experimental":[167],"results":[168],"show":[169],"that":[170],"compared":[171],"previous":[173],"competitive":[174],"methods,":[175],"our":[176,205,215],"method":[177],"reduces":[178],"least":[180],"72%":[181],"run":[182],"time":[183],"while":[184],"achieving":[185],"better":[186],"image":[187],"synthesis":[188],"quality":[189,213],"based":[190],"both":[192],"subjective":[193],"objective":[195],"evaluation":[196],"metrics.":[197],"Ablation":[198],"validate":[200],"major":[202],"contribution":[203],"re-stylization":[210],"synthesized":[216],"images.":[217]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}