{"id":"https://openalex.org/W3009606699","doi":"https://doi.org/10.1109/wacv45572.2020.9093393","title":"Variational Image Deraining","display_name":"Variational Image Deraining","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3009606699","doi":"https://doi.org/10.1109/wacv45572.2020.9093393","mag":"3009606699"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093393","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/A5077690631","display_name":"Yingjun Du","orcid":"https://orcid.org/0000-0001-7537-6457"},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Yingjun Du","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042967567","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0002-1602-538X"},"institutions":[{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["Inception Institute of Artificial Intelligence, Abu Dhabi, UAE"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, UAE","institution_ids":["https://openalex.org/I4210116052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101992408","display_name":"Qiang Qiu","orcid":"https://orcid.org/0000-0003-2610-3502"},"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":"Qiang Qiu","raw_affiliation_strings":["Duke University, Durham, USA"],"affiliations":[{"raw_affiliation_string":"Duke University, Durham, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026486701","display_name":"Xiantong Zhen","orcid":"https://orcid.org/0000-0001-5213-0462"},"institutions":[{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Xiantong Zhen","raw_affiliation_strings":["Inception Institute of Artificial Intelligence, Abu Dhabi, UAE"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, UAE","institution_ids":["https://openalex.org/I4210116052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100433899","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-2078-4215"},"institutions":[{"id":"https://openalex.org/I4210128140","display_name":"Guangdong University of Petrochemical Technology","ror":"https://ror.org/030ffke25","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128140"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Guangdong University of Petrochemical Technology, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Guangdong University of Petrochemical Technology, Guangdong, China","institution_ids":["https://openalex.org/I4210128140"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5077690631"],"corresponding_institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":3.224,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93328628,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2395","last_page":"2404"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991999864578247,"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":0.9973000288009644,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6825022101402283},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6606253385543823},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6414607763290405},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5791968107223511},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5764332413673401},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5264961123466492},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5233351588249207},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46133244037628174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35775837302207947},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08468392491340637}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6825022101402283},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6606253385543823},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6414607763290405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5791968107223511},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5764332413673401},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5264961123466492},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5233351588249207},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46133244037628174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35775837302207947},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08468392491340637},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093393","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":[{"id":"https://metadata.un.org/sdg/11","score":0.5699999928474426,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1909320841","https://openalex.org/W1921523184","https://openalex.org/W1959608418","https://openalex.org/W2055438706","https://openalex.org/W2089961441","https://openalex.org/W2121396509","https://openalex.org/W2128254161","https://openalex.org/W2133665775","https://openalex.org/W2154621477","https://openalex.org/W2166851633","https://openalex.org/W2188365844","https://openalex.org/W2209874411","https://openalex.org/W2466666260","https://openalex.org/W2470142083","https://openalex.org/W2509784253","https://openalex.org/W2559264300","https://openalex.org/W2580458810","https://openalex.org/W2584890299","https://openalex.org/W2613034492","https://openalex.org/W2740543610","https://openalex.org/W2740982616","https://openalex.org/W2778532031","https://openalex.org/W2820727372","https://openalex.org/W2884068670","https://openalex.org/W2887738788","https://openalex.org/W2912435603","https://openalex.org/W2949117887","https://openalex.org/W2962963674","https://openalex.org/W2963017889","https://openalex.org/W2963150697","https://openalex.org/W2963315679","https://openalex.org/W2963446712","https://openalex.org/W2963795951","https://openalex.org/W2963878020","https://openalex.org/W2964121744","https://openalex.org/W2964212750","https://openalex.org/W3020882730","https://openalex.org/W4294562888","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6639732818","https://openalex.org/W6640185926","https://openalex.org/W6640963894","https://openalex.org/W6684578138","https://openalex.org/W6687045409","https://openalex.org/W6719953051","https://openalex.org/W6732779862","https://openalex.org/W6748102919","https://openalex.org/W6753715905","https://openalex.org/W6753755972","https://openalex.org/W6765732119"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W4390516098","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008"],"abstract_inverted_index":{"Images":[0],"captured":[1],"in":[2,69],"severe":[3],"weather":[4],"such":[5],"as":[6],"rain":[7,39,81],"and":[8,98,147],"snow":[9],"significantly":[10],"degrade":[11],"the":[12,36,46,137],"accuracy":[13],"of":[14],"vision":[15],"systems,":[16],"e.g.,":[17],"for":[18,89],"outdoor":[19],"video":[20],"surveillance":[21],"or":[22],"autonomous":[23],"driving.":[24],"Image":[25],"deraining":[26,62,68,78,125,139],"is":[27],"a":[28,59,70,85],"critical":[29],"yet":[30],"highly":[31],"challenging":[32],"task,":[33],"due":[34],"to":[35,79,103,121],"fact":[37],"that":[38,115,136],"density":[40,86],"varies":[41],"across":[42,51],"spatial":[43,80],"locations,":[44],"while":[45],"distribution":[47],"patterns":[48],"simultaneously":[49],"vary":[50],"color":[52,91,128],"channels.":[53],"In":[54,101],"this":[55],"paper,":[56],"we":[57,83,107],"propose":[58],"variational":[60,72],"image":[61,67],"(VID)":[63],"method":[64,140],"by":[65,112,155],"formulating":[66],"conditional":[71],"auto-encoder":[73],"framework.":[74],"To":[75],"achieve":[76],"adaptive":[77],"density,":[82],"generate":[84],"estimation":[87],"map":[88],"each":[90],"channel,":[92],"which":[93],"can":[94],"largely":[95],"avoid":[96],"over":[97],"under":[99],"deraining.":[100],"addition,":[102],"address":[104],"cross-channel":[105],"variations,":[106],"conduct":[108],"channel-wise":[109],"deraining,":[110],"motivated":[111],"our":[113],"observation":[114],"bright":[116,123],"pixels":[117],"do":[118],"not":[119],"tend":[120],"remain":[122],"after":[124],"unless":[126],"their":[127],"channels":[129],"are":[130],"handled":[131],"separately.":[132],"Experimental":[133],"results":[134],"show":[135],"proposed":[138],"achieves":[141],"superior":[142],"performance":[143],"on":[144],"both":[145],"synthesized":[146],"real":[148],"rainy":[149],"images,":[150],"surpassing":[151],"previous":[152],"state-of-the-art":[153],"methods":[154],"large":[156],"margins.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}