{"id":"https://openalex.org/W2963767233","doi":"https://doi.org/10.1145/3272127.3275081","title":"Image smoothing via unsupervised learning","display_name":"Image smoothing via unsupervised learning","publication_year":2018,"publication_date":"2018-11-28","ids":{"openalex":"https://openalex.org/W2963767233","doi":"https://doi.org/10.1145/3272127.3275081","mag":"2963767233"},"language":"en","primary_location":{"id":"doi:10.1145/3272127.3275081","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3272127.3275081","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-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/A5030729327","display_name":"Qingnan Fan","orcid":"https://orcid.org/0000-0003-1249-2826"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingnan Fan","raw_affiliation_strings":["Shandong University"],"affiliations":[{"raw_affiliation_string":"Shandong University","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076804411","display_name":"Jiaolong Yang","orcid":"https://orcid.org/0000-0002-7314-6567"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaolong Yang","raw_affiliation_strings":["Microsoft Research Asia"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085016531","display_name":"David Wipf","orcid":"https://orcid.org/0000-0002-2768-4540"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"David Wipf","raw_affiliation_strings":["Microsoft Research Asia"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010714340","display_name":"Baoquan Chen","orcid":"https://orcid.org/0000-0003-4702-036X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"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":"Baoquan Chen","raw_affiliation_strings":["Peking University, Shandong University"],"affiliations":[{"raw_affiliation_string":"Peking University, Shandong University","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100784734","display_name":"Xin Tong","orcid":"https://orcid.org/0000-0001-8788-2453"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Tong","raw_affiliation_strings":["Microsoft Research Asia"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030729327"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":7.3301,"has_fulltext":false,"cited_by_count":137,"citation_normalized_percentile":{"value":0.97883323,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"37","issue":"6","first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9986000061035156,"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/smoothing","display_name":"Smoothing","score":0.8515982627868652},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7989962100982666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6219230890274048},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.5504952669143677},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5314836502075195},{"id":"https://openalex.org/keywords/edge-preserving-smoothing","display_name":"Edge-preserving smoothing","score":0.5214890241622925},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.486767053604126},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.434734046459198},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.432281494140625},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.42961281538009644},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4262838065624237},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37522968649864197},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3272343873977661},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32456856966018677},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.10581770539283752}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.8515982627868652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7989962100982666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6219230890274048},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.5504952669143677},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5314836502075195},{"id":"https://openalex.org/C141651230","wikidata":"https://www.wikidata.org/wiki/Q5337637","display_name":"Edge-preserving smoothing","level":4,"score":0.5214890241622925},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.486767053604126},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.434734046459198},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.432281494140625},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.42961281538009644},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4262838065624237},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37522968649864197},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3272343873977661},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32456856966018677},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.10581770539283752},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3272127.3275081","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3272127.3275081","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W361146540","https://openalex.org/W1528144695","https://openalex.org/W1647921945","https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1878947057","https://openalex.org/W1918250297","https://openalex.org/W1972292376","https://openalex.org/W1979369422","https://openalex.org/W1993465480","https://openalex.org/W2009576740","https://openalex.org/W2015207482","https://openalex.org/W2016163842","https://openalex.org/W2016787456","https://openalex.org/W2019904315","https://openalex.org/W2031489346","https://openalex.org/W2033250440","https://openalex.org/W2039755782","https://openalex.org/W2050551672","https://openalex.org/W2061052400","https://openalex.org/W2061702899","https://openalex.org/W2078718577","https://openalex.org/W2080794127","https://openalex.org/W2096768337","https://openalex.org/W2099244020","https://openalex.org/W2109075629","https://openalex.org/W2125189371","https://openalex.org/W2126043703","https://openalex.org/W2138265962","https://openalex.org/W2141957843","https://openalex.org/W2146578165","https://openalex.org/W2150134853","https://openalex.org/W2194775991","https://openalex.org/W2209692720","https://openalex.org/W2231495490","https://openalex.org/W2242218935","https://openalex.org/W2519373937","https://openalex.org/W2573726823","https://openalex.org/W2603351312","https://openalex.org/W2604737827","https://openalex.org/W2735974062","https://openalex.org/W2802247885","https://openalex.org/W2809852002","https://openalex.org/W2949960002","https://openalex.org/W2952972288","https://openalex.org/W2963032190","https://openalex.org/W2963452532","https://openalex.org/W2963676366","https://openalex.org/W2963840672","https://openalex.org/W2963920720","https://openalex.org/W2964013315","https://openalex.org/W2964121744","https://openalex.org/W2996868574","https://openalex.org/W3125028070","https://openalex.org/W3138063419","https://openalex.org/W3139167831","https://openalex.org/W4247811648"],"related_works":["https://openalex.org/W4213275102","https://openalex.org/W2031490378","https://openalex.org/W2151138761","https://openalex.org/W1591640974","https://openalex.org/W1520441540","https://openalex.org/W4294651008","https://openalex.org/W2888823469","https://openalex.org/W2978930127","https://openalex.org/W3037144611","https://openalex.org/W2383399164"],"abstract_inverted_index":{"Image":[0],"smoothing":[1,31,91,100],"represents":[2],"a":[3,19,54,73,95,140],"fundamental":[4],"component":[5],"of":[6,46,83,98],"many":[7],"disparate":[8],"computer":[9],"vision":[10],"and":[11,29,72,119,123],"graphics":[12],"applications.":[13],"In":[14],"this":[15],"paper,":[16],"we":[17],"present":[18],"unified":[20,104],"unsupervised":[21],"(label-free)":[22],"learning":[23,35],"framework":[24,105],"that":[25,58],"facilitates":[26],"generating":[27],"flexible":[28],"high-quality":[30],"effects":[32],"by":[33],"directly":[34],"from":[36],"data":[37],"using":[38],"deep":[39],"convolutional":[40],"neural":[41],"networks":[42],"(CNNs).":[43],"The":[44],"heart":[45],"the":[47,50,103],"design":[48],"is":[49,136],"training":[51],"signal":[52],"as":[53],"novel":[55],"energy":[56],"function":[57],"includes":[59],"an":[60],"edge-preserving":[61],"regularizer":[62],"which":[63,79],"helps":[64],"maintain":[65],"important":[66],"yet":[67],"potentially":[68],"vulnerable":[69],"image":[70,87,99,111,121],"structures,":[71],"spatially-adaptive":[74],"L":[75],"p":[76],"flattening":[77],"criterion":[78],"imposes":[80],"different":[81,86],"forms":[82],"regularization":[84],"onto":[85],"regions":[88],"for":[89,146],"better":[90,129],"quality.":[92],"We":[93],"implement":[94],"diverse":[96],"set":[97],"solutions":[101],"employing":[102],"targeting":[106],"various":[107],"applications":[108],"such":[109],"as,":[110],"abstraction,":[112],"pencil":[113],"sketching,":[114],"detail":[115],"enhancement,":[116],"texture":[117],"removal":[118],"content-aware":[120],"manipulation,":[122],"obtain":[124],"results":[125],"comparable":[126],"with":[127,139],"or":[128],"than":[130],"previous":[131],"methods.":[132],"Moreover,":[133],"our":[134],"method":[135],"extremely":[137],"fast":[138],"modern":[141],"GPU":[142],"(e.g,":[143],"200":[144],"fps":[145],"1280\u00d7720":[147],"images).":[148]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
