{"id":"https://openalex.org/W3009313482","doi":"https://doi.org/10.1109/wacv45572.2020.9093529","title":"DAVID: Dual-Attentional Video Deblurring","display_name":"DAVID: Dual-Attentional Video Deblurring","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3009313482","doi":"https://doi.org/10.1109/wacv45572.2020.9093529","mag":"3009313482"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","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/A5029597925","display_name":"Junru Wu","orcid":"https://orcid.org/0009-0000-5586-6926"},"institutions":[{"id":"https://openalex.org/I2801613365","display_name":"Mitchell Institute","ror":"https://ror.org/03ds72003","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2801613365"]},{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junru Wu","raw_affiliation_strings":["Texas A&M University"],"affiliations":[{"raw_affiliation_string":"Texas A&M University","institution_ids":["https://openalex.org/I2801613365","https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101595454","display_name":"Yu Xiang","orcid":"https://orcid.org/0000-0002-2891-9153"},"institutions":[{"id":"https://openalex.org/I4210107353","display_name":"NEC (United States)","ror":"https://ror.org/01v791m31","country_code":"US","type":"company","lineage":["https://openalex.org/I118347220","https://openalex.org/I4210107353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Yu","raw_affiliation_strings":["NEC Laboratories America"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories America","institution_ids":["https://openalex.org/I4210107353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101522028","display_name":"Ding Liu","orcid":"https://orcid.org/0000-0002-2070-9661"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding Liu","raw_affiliation_strings":["ByteDance AI Lab"],"affiliations":[{"raw_affiliation_string":"ByteDance AI Lab","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046609009","display_name":"Manmohan Chandraker","orcid":"https://orcid.org/0000-0003-4683-2454"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manmohan Chandraker","raw_affiliation_strings":["University of California, San Diego"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhangyang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2801613365","display_name":"Mitchell Institute","ror":"https://ror.org/03ds72003","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2801613365"]},{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhangyang Wang","raw_affiliation_strings":["Texas A&M University"],"affiliations":[{"raw_affiliation_string":"Texas A&M University","institution_ids":["https://openalex.org/I2801613365","https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029597925"],"corresponding_institution_ids":["https://openalex.org/I2801613365","https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":2.1589,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.89456014,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2365","last_page":"2374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing 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/T11105","display_name":"Advanced Image Processing 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/T10531","display_name":"Advanced Vision and Imaging","score":0.9976000189781189,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9918000102043152,"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/deblurring","display_name":"Deblurring","score":0.9696469306945801},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.81175297498703},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7055445313453674},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.7010027170181274},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6914029121398926},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6619497537612915},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5764427781105042},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.4758464992046356},{"id":"https://openalex.org/keywords/shake","display_name":"Shake","score":0.4737872779369354},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4737352132797241},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.28106188774108887},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2795589566230774},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.18540877103805542}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9696469306945801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81175297498703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7055445313453674},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.7010027170181274},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6914029121398926},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6619497537612915},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5764427781105042},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.4758464992046356},{"id":"https://openalex.org/C2779053110","wikidata":"https://www.wikidata.org/wiki/Q7462601","display_name":"Shake","level":2,"score":0.4737872779369354},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4737352132797241},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.28106188774108887},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2795589566230774},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.18540877103805542},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/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/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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W1457323852","https://openalex.org/W1484210532","https://openalex.org/W1522301498","https://openalex.org/W1604428010","https://openalex.org/W1901129140","https://openalex.org/W1916935112","https://openalex.org/W1935182534","https://openalex.org/W1987075379","https://openalex.org/W2043529138","https://openalex.org/W2044005793","https://openalex.org/W2054619618","https://openalex.org/W2062679213","https://openalex.org/W2118456997","https://openalex.org/W2124964692","https://openalex.org/W2132244934","https://openalex.org/W2138204001","https://openalex.org/W2141115311","https://openalex.org/W2151109506","https://openalex.org/W2167307343","https://openalex.org/W2169574628","https://openalex.org/W2396267364","https://openalex.org/W2468652750","https://openalex.org/W2471801048","https://openalex.org/W2474628748","https://openalex.org/W2505121268","https://openalex.org/W2560533888","https://openalex.org/W2605737038","https://openalex.org/W2609107023","https://openalex.org/W2626739722","https://openalex.org/W2729222819","https://openalex.org/W2738579427","https://openalex.org/W2756389006","https://openalex.org/W2780624730","https://openalex.org/W2781335552","https://openalex.org/W2804078698","https://openalex.org/W2913508739","https://openalex.org/W2939502864","https://openalex.org/W2945823804","https://openalex.org/W2948208276","https://openalex.org/W2963312584","https://openalex.org/W2963403868","https://openalex.org/W2963507202","https://openalex.org/W2963559058","https://openalex.org/W2963661589","https://openalex.org/W2963945023","https://openalex.org/W2964030969","https://openalex.org/W2964040059","https://openalex.org/W2964051148","https://openalex.org/W2964121744","https://openalex.org/W2964251418","https://openalex.org/W2982795046","https://openalex.org/W2985805335","https://openalex.org/W2990827756","https://openalex.org/W2991232432","https://openalex.org/W4385245566","https://openalex.org/W6628927728","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6678856934","https://openalex.org/W6682344109","https://openalex.org/W6687461059","https://openalex.org/W6720275808","https://openalex.org/W6724782142","https://openalex.org/W6730518680","https://openalex.org/W6739806132","https://openalex.org/W6739901393","https://openalex.org/W6740374193","https://openalex.org/W6745853359","https://openalex.org/W6752378368","https://openalex.org/W6758579525","https://openalex.org/W6761264711","https://openalex.org/W6762789347","https://openalex.org/W6769737877","https://openalex.org/W7006583108"],"related_works":["https://openalex.org/W4224288641","https://openalex.org/W4382450485","https://openalex.org/W2557898294","https://openalex.org/W2232201529","https://openalex.org/W2558246008","https://openalex.org/W4293737289","https://openalex.org/W2121853623","https://openalex.org/W4388209117","https://openalex.org/W4224029260","https://openalex.org/W4297097661"],"abstract_inverted_index":{"Blind":[0],"video":[1,142,188],"deblurring":[2,75],"restores":[3],"sharp":[4,96,108],"frames":[5,146],"from":[6,111,138],"a":[7,15,44,65,133],"blurry":[8],"sequence":[9],"without":[10],"any":[11],"prior.":[12],"It":[13],"is":[14,29],"challenging":[16,160],"task":[17],"because":[18],"the":[19,89,95,139,168,180],"blur":[20,119,128],"due":[21],"to":[22,69],"camera":[23],"shake,":[24],"object":[25],"movement":[26],"and":[27,34,49,105,123,175],"defocusing":[28],"heterogeneous":[30],"in":[31,185],"both":[32],"temporal":[33,72,91,149],"spatial":[35],"dimensions.":[36],"Traditional":[37],"methods":[38],"train":[39,122],"on":[40,125,157,167],"datasets":[41],"synthesized":[42],"with":[43,76,147],"single":[45],"level":[46],"of":[47,57,182],"blur,":[48],"thus":[50],"do":[51],"not":[52],"generalize":[53],"well":[54],"across":[55],"levels":[56],"blurriness.":[58],"To":[59,121],"address":[60],"this":[61,158],"challenge,":[62],"we":[63,131],"propose":[64,132],"dual":[66],"attention":[67,85,101,114],"mechanism":[68],"dynamically":[70],"aggregate":[71],"cues":[73],"for":[74,93,117],"an":[77,83],"end-to-end":[78],"trainable":[79],"network":[80],"structure.":[81],"Specifically,":[82],"internal":[84,113],"module":[86,102],"adaptively":[87,103],"selects":[88],"optimal":[90],"scales":[92],"restoring":[94],"center":[97],"frame.":[98],"An":[99],"external":[100],"aggregates":[104],"refines":[106],"multiple":[107],"frame":[109],"estimates,":[110],"several":[112],"modules":[115],"designed":[116],"different":[118,148],"levels.":[120],"evaluate":[124],"more":[126,159],"diverse":[127],"severity":[129],"levels,":[130],"Challenging":[134],"DVD":[135,141,170],"dataset":[136,161],"generated":[137],"raw":[140],"set":[143],"by":[144],"pooling":[145],"windows.":[150],"Our":[151],"framework":[152],"achieves":[153],"consistently":[154],"better":[155],"performance":[156],"while":[162],"obtaining":[163],"strongly":[164],"competitive":[165],"results":[166],"original":[169],"benchmark.":[171],"Extensive":[172],"ablative":[173],"studies":[174],"qualitative":[176],"visualizations":[177],"further":[178],"demonstrate":[179],"advantage":[181],"our":[183],"method":[184],"handling":[186],"real":[187],"blur.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}