{"id":"https://openalex.org/W2965669158","doi":"https://doi.org/10.1109/cvprw.2019.00247","title":"EDVR: Video Restoration With Enhanced Deformable Convolutional Networks","display_name":"EDVR: Video Restoration With Enhanced Deformable Convolutional Networks","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2965669158","doi":"https://doi.org/10.1109/cvprw.2019.00247","mag":"2965669158"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2019.00247","doi":"https://doi.org/10.1109/cvprw.2019.00247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2019.00247","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"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,"listed_in":[],"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":"2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5101538534","display_name":"Xintao Wang","orcid":"https://orcid.org/0000-0001-6585-8604","observed_orcids":["https://orcid.org/0000-0001-6585-8604"]},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xintao Wang","raw_affiliation_strings":["CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007227485","display_name":"Kelvin C. K. Chan","orcid":"https://orcid.org/0000-0002-5456-8991","observed_orcids":["https://orcid.org/0000-0002-5456-8991"]},"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":"Kelvin C.K. Chan","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100719460","display_name":"Ke Yu","orcid":"https://orcid.org/0009-0005-2034-6177","observed_orcids":["https://orcid.org/0009-0005-2034-6177","https://orcid.org/0000-0002-4185-5668"]},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ke Yu","raw_affiliation_strings":["CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023845728","display_name":"Chao Dong","orcid":"https://orcid.org/0000-0003-2260-8079","observed_orcids":["https://orcid.org/0000-0003-2260-8079"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Dong","raw_affiliation_strings":["SIAT-SenseTime Joint Lab, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIAT-SenseTime Joint Lab, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005626854","display_name":"Chen Change Loy","orcid":"https://orcid.org/0000-0001-5345-1591","observed_orcids":["https://orcid.org/0000-0001-5345-1591"]},"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":"Chen Change Loy","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":42.0313,"has_fulltext":false,"cited_by_count":1302,"citation_normalized_percentile":{"value":0.99791232,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1954","last_page":"1963"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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":0.0003000000142492354,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00019999999494757503,"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/video-restoration","display_name":"video restoration","score":0.9940000176429749},{"id":"https://openalex.org/keywords/video-super-resolution","display_name":"video super-resolution","score":0.8989999890327454},{"id":"https://openalex.org/keywords/video-deblurring","display_name":"video deblurring","score":0.9639999866485596},{"id":"https://openalex.org/keywords/deformable-convolution","display_name":"deformable convolution","score":0.9229999780654907},{"id":"https://openalex.org/keywords/frame-alignment","display_name":"frame alignment","score":0.9120000004768372},{"id":"https://openalex.org/keywords/coarse-to-fine-alignment","display_name":"coarse-to-fine alignment","score":0.8259999752044678},{"id":"https://openalex.org/keywords/frame-fusion","display_name":"frame fusion","score":0.7699999809265137},{"id":"https://openalex.org/keywords/large-motion","display_name":"large motion","score":0.6179999709129333}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.903131902217865},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8105231523513794},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7630386352539062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6910127401351929},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6291738152503967},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.622568666934967},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6099292039871216},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5599796175956726},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5261164307594299},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4610215127468109},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.45861247181892395},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.45651933550834656},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.45508649945259094},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44475340843200684},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.42013275623321533},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2051302194595337},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.15768316388130188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09831419587135315},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvprw.2019.00247","doi":"https://doi.org/10.1109/cvprw.2019.00247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2019.00247","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"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,"listed_in":[],"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":"2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W1522301498","https://openalex.org/W1913633284","https://openalex.org/W1979606177","https://openalex.org/W2010981316","https://openalex.org/W2109586214","https://openalex.org/W2210480155","https://openalex.org/W2263468737","https://openalex.org/W2295865687","https://openalex.org/W2320725294","https://openalex.org/W2548527721","https://openalex.org/W2557227117","https://openalex.org/W2560474170","https://openalex.org/W2560533888","https://openalex.org/W2601564443","https://openalex.org/W2605737038","https://openalex.org/W2607041014","https://openalex.org/W2626778328","https://openalex.org/W2707890836","https://openalex.org/W2735224642","https://openalex.org/W2738579427","https://openalex.org/W2739757502","https://openalex.org/W2768546798","https://openalex.org/W2781335552","https://openalex.org/W2783348085","https://openalex.org/W2796314858","https://openalex.org/W2798664922","https://openalex.org/W2866634454","https://openalex.org/W2884585870","https://openalex.org/W2891158090","https://openalex.org/W2891446678","https://openalex.org/W2891511203","https://openalex.org/W2895361760","https://openalex.org/W2923834406","https://openalex.org/W2951291220","https://openalex.org/W2953823547","https://openalex.org/W2962737939","https://openalex.org/W2963091558","https://openalex.org/W2963470893","https://openalex.org/W2963782415","https://openalex.org/W2963814095","https://openalex.org/W2964030969","https://openalex.org/W2964040059","https://openalex.org/W2964042483","https://openalex.org/W2964086649","https://openalex.org/W2964121744","https://openalex.org/W2964156315","https://openalex.org/W2964343197","https://openalex.org/W2966926453","https://openalex.org/W3007471652","https://openalex.org/W3034475761","https://openalex.org/W3102015846"],"related_works":["https://openalex.org/W4392543517","https://openalex.org/W4312236735","https://openalex.org/W7133203186","https://openalex.org/W4223597402","https://openalex.org/W4416242907","https://openalex.org/W4410050521","https://openalex.org/W4221159600","https://openalex.org/W3026900437","https://openalex.org/W4402727316","https://openalex.org/W3034475761"],"abstract_inverted_index":{"Video":[0,65],"restoration":[1,165],"tasks,":[2],"including":[3],"super-resolution,":[4],"deblurring,":[5],"etc,":[6],"are":[7],"drawing":[8],"increasing":[9],"attention":[10,123],"in":[11,23,93,106,121,157,161],"the":[12,24,100,146,150,162],"computer":[13],"vision":[14],"community.":[15],"A":[16],"challenging":[17],"benchmark":[18,29],"named":[19],"REDS":[20],"is":[21,97,124,185],"released":[22],"NTIRE19":[25,163],"Challenge.":[26],"This":[27],"new":[28],"challenges":[30],"existing":[31],"methods":[32,177],"from":[33],"two":[34],"aspects:":[35],"(1)":[36],"how":[37,47],"to":[38,48,74,79,132,140,174],"align":[39],"multiple":[40],"frames":[41,52],"given":[42],"large":[43,81,155],"motions,":[44,82],"and":[45,56,88,115,128,148,166,181],"(2)":[46],"effectively":[49],"fuse":[50],"different":[51],"with":[53,68],"diverse":[54],"motion":[55],"blur.":[57],"In":[58],"this":[59],"work,":[60],"we":[61,83,111],"propose":[62,112],"a":[63,85,107,113,154],"novel":[64],"Restoration":[66],"framework":[67],"Enhanced":[69],"Deformable":[70,89],"convolutions,":[71],"termed":[72],"EDVR,":[73],"address":[75],"these":[76,141],"challenges.":[77,168],"First,":[78],"handle":[80],"devise":[84],"Pyramid,":[86],"Cascading":[87],"(PCD)":[90],"alignment":[91,96],"module,":[92,120],"which":[94,122],"frame":[95],"done":[98],"at":[99,187],"feature":[101],"level":[102],"using":[103],"deformable":[104],"convolutions":[105],"coarse-to-fine":[108],"manner.":[109],"Second,":[110],"Temporal":[114],"Spatial":[116],"Attention":[117],"(TSA)":[118],"fusion":[119],"applied":[125],"both":[126],"temporally":[127],"spatially,":[129],"so":[130],"as":[131],"emphasize":[133],"important":[134],"features":[135],"for":[136],"subsequent":[137],"restoration.":[138],"Thanks":[139],"modules,":[142],"our":[143],"EDVR":[144,169],"wins":[145],"champions":[147],"outperforms":[149],"second":[151],"place":[152],"by":[153],"margin":[156],"all":[158],"four":[159],"tracks":[160],"video":[164,179],"enhancement":[167],"also":[170],"demonstrates":[171],"superior":[172],"performance":[173],"state-of-the-art":[175],"published":[176],"on":[178],"super-resolution":[180],"deblurring.":[182],"The":[183],"code":[184],"available":[186],"https://github.com/xinntao/EDVR.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":126},{"year":2025,"cited_by_count":191},{"year":2024,"cited_by_count":232},{"year":2023,"cited_by_count":233},{"year":2022,"cited_by_count":207},{"year":2021,"cited_by_count":204},{"year":2020,"cited_by_count":96},{"year":2019,"cited_by_count":13}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2019-08-13T00:00:00"}