{"id":"https://openalex.org/W4292828918","doi":"https://doi.org/10.1109/cvprw56347.2022.00069","title":"Exploiting Distortion Information for Multi-degraded Image Restoration","display_name":"Exploiting Distortion Information for Multi-degraded Image Restoration","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4292828918","doi":"https://doi.org/10.1109/cvprw56347.2022.00069"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw56347.2022.00069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw56347.2022.00069","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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/A5032411063","display_name":"Wooksu Shin","orcid":null},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Wooksu Shin","raw_affiliation_strings":["Ajou University,Department of Artificial Intelligence","Department of Artificial Intelligence, Ajou University"],"affiliations":[{"raw_affiliation_string":"Ajou University,Department of Artificial Intelligence","institution_ids":["https://openalex.org/I57664883"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Ajou University","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047656074","display_name":"Namhyuk Ahn","orcid":"https://orcid.org/0000-0003-1990-9516"},"institutions":[{"id":"https://openalex.org/I60922564","display_name":"Naver (South Korea)","ror":"https://ror.org/04nzrnx83","country_code":"KR","type":"company","lineage":["https://openalex.org/I60922564"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Namhyuk Ahn","raw_affiliation_strings":["Naver Webtoon AI"],"affiliations":[{"raw_affiliation_string":"Naver Webtoon AI","institution_ids":["https://openalex.org/I60922564"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051011750","display_name":"Jeong-Hyeon Moon","orcid":"https://orcid.org/0000-0002-2805-7063"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeong-Hyeon Moon","raw_affiliation_strings":["Ajou University,Department of Artificial Intelligence","Department of Artificial Intelligence, Ajou University"],"affiliations":[{"raw_affiliation_string":"Ajou University,Department of Artificial Intelligence","institution_ids":["https://openalex.org/I57664883"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Ajou University","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068333871","display_name":"Kyung-Ah Sohn","orcid":"https://orcid.org/0000-0001-8941-1188"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyung-Ah Sohn","raw_affiliation_strings":["Ajou University,Department of Artificial Intelligence","Department of Artificial Intelligence, Ajou University"],"affiliations":[{"raw_affiliation_string":"Ajou University,Department of Artificial Intelligence","institution_ids":["https://openalex.org/I57664883"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Ajou University","institution_ids":["https://openalex.org/I57664883"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032411063"],"corresponding_institution_ids":["https://openalex.org/I57664883"],"apc_list":null,"apc_paid":null,"fwci":0.6622,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.7806217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"536","last_page":"545"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9959999918937683,"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":0.9952999949455261,"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/distortion","display_name":"Distortion (music)","score":0.9070773124694824},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6435242295265198},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.6008827090263367},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5759903192520142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5380316376686096},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33732205629348755},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3218027353286743},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.25111377239227295},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07950863242149353}],"concepts":[{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.9070773124694824},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6435242295265198},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6008827090263367},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5759903192520142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5380316376686096},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33732205629348755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3218027353286743},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25111377239227295},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07950863242149353},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvprw56347.2022.00069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw56347.2022.00069","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W2037642501","https://openalex.org/W2242218935","https://openalex.org/W2508457857","https://openalex.org/W2560533888","https://openalex.org/W2630837129","https://openalex.org/W2739757502","https://openalex.org/W2741137940","https://openalex.org/W2798735168","https://openalex.org/W2799192307","https://openalex.org/W2866634454","https://openalex.org/W2932253358","https://openalex.org/W2941471678","https://openalex.org/W2962767526","https://openalex.org/W2963312584","https://openalex.org/W2963372104","https://openalex.org/W2963645458","https://openalex.org/W2963814095","https://openalex.org/W2964030969","https://openalex.org/W2964268638","https://openalex.org/W2964297221","https://openalex.org/W2964343197","https://openalex.org/W2983315964","https://openalex.org/W2983467712","https://openalex.org/W2984447413","https://openalex.org/W2987150909","https://openalex.org/W3001778788","https://openalex.org/W3003661405","https://openalex.org/W3034448817","https://openalex.org/W3034595214","https://openalex.org/W3035484352","https://openalex.org/W3097169367","https://openalex.org/W3106758205","https://openalex.org/W3108114584","https://openalex.org/W3108452013","https://openalex.org/W3168684807","https://openalex.org/W3175634226","https://openalex.org/W3176234575","https://openalex.org/W3203631022","https://openalex.org/W3204971388","https://openalex.org/W4214609808","https://openalex.org/W4225672218","https://openalex.org/W4288404646","https://openalex.org/W4288419382","https://openalex.org/W6602211262","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6690498163","https://openalex.org/W6739696289","https://openalex.org/W6748551697","https://openalex.org/W6749061506","https://openalex.org/W6750493494","https://openalex.org/W6753074096","https://openalex.org/W6757555829","https://openalex.org/W6765577132","https://openalex.org/W6772892274","https://openalex.org/W6773063408","https://openalex.org/W6775092777","https://openalex.org/W6783686316","https://openalex.org/W6783739785","https://openalex.org/W6803518762"],"related_works":["https://openalex.org/W2357322570","https://openalex.org/W2997591215","https://openalex.org/W2227541280","https://openalex.org/W2029783634","https://openalex.org/W2328889547","https://openalex.org/W2979181971","https://openalex.org/W2888591766","https://openalex.org/W1598401975","https://openalex.org/W2365681766","https://openalex.org/W2393963626"],"abstract_inverted_index":{"In":[0,57,123],"recent":[1],"years,":[2],"tremendous":[3],"studies":[4,45],"have":[5,18,46],"been":[6],"performed":[7],"on":[8,65],"the":[9,42,52,62,66,82,94,110,120,129,133,146],"image":[10,31],"distortion":[11,28,88,96,111,147],"restoration":[12,90,121],"task":[13],"and":[14,69,113,116,135],"deep":[15],"learning-based":[16],"methods":[17],"shown":[19],"prominent":[20],"performance":[21],"improvement.":[22],"However,":[23],"assuming":[24],"only":[25],"a":[26,71,76,87,100],"single":[27],"to":[29,119],"an":[30],"may":[32],"not":[33],"be":[34],"applicable":[35],"in":[36],"many":[37],"real-world":[38],"scenarios.":[39],"To":[40,80,103],"mitigate":[41],"issue,":[43],"some":[44],"proposed":[47,130],"multi-distortion":[48,67,78,83],"datasets":[49],"by":[50],"applying":[51],"corruptions":[53],"sequentially":[54],"or":[55],"spatially.":[56],"this":[58],"work,":[59],"we":[60,85,126,136],"integrate":[61],"two":[63],"perspectives":[64],"nature":[68],"propose":[70],"new":[72],"dataset":[73],"that":[74,128,139],"is":[75],"holistic":[77],"dataset.":[79],"restore":[81],"effectively,":[84],"introduce":[86],"information-guided":[89],"network,":[91],"which":[92],"exploits":[93],"conditional":[95],"information":[97,148],"when":[98],"reconstructing":[99],"given":[101],"image.":[102],"do":[104],"that,":[105],"our":[106,124],"framework":[107],"first":[108],"predicts":[109],"type":[112],"their":[114],"strength":[115],"delivers":[117],"these":[118],"module.":[122],"experiments,":[125],"show":[127],"model":[131],"exceeds":[132],"others":[134],"also":[137],"demonstrate":[138],"any":[140],"backbone":[141],"network":[142],"benefits":[143],"from":[144],"receiving":[145],"as":[149],"prior":[150],"knowledge.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}