{"id":"https://openalex.org/W3035599625","doi":"https://doi.org/10.1109/tip.2020.3000612","title":"Single Image Deraining Using Time-Lapse Data","display_name":"Single Image Deraining Using Time-Lapse Data","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3035599625","doi":"https://doi.org/10.1109/tip.2020.3000612","mag":"3035599625"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.3000612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3000612","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://infoscience.epfl.ch/record/279357","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020958022","display_name":"Jaehoon Cho","orcid":"https://orcid.org/0000-0002-4093-2262"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaehoon Cho","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4093-2262","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085363061","display_name":"Seungryong Kim","orcid":"https://orcid.org/0000-0003-2927-6273"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","KR"],"is_corresponding":false,"raw_author_name":"Seungryong Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Korea University, Seoul, South Korea","\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Lausanne, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037006973","display_name":"Dongbo Min","orcid":"https://orcid.org/0000-0003-4825-5240"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongbo Min","raw_affiliation_strings":["Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4825-5240","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea","institution_ids":["https://openalex.org/I138925566"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073320959","display_name":"Kwanghoon Sohn","orcid":"https://orcid.org/0000-0002-3715-0331"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kwanghoon Sohn","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-3715-0331","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020958022"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":0.6868,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.71737184,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"29","issue":null,"first_page":"7274","last_page":"7289"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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":1.0,"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":0.9991000294685364,"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":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.741074800491333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6586089730262756},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5659971833229065},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5246572494506836},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5172170400619507},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5020473003387451},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47980359196662903},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4380035400390625},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3437066972255707},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15996745228767395}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741074800491333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6586089730262756},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5659971833229065},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5246572494506836},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5172170400619507},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5020473003387451},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47980359196662903},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4380035400390625},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3437066972255707},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15996745228767395},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2020.3000612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3000612","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:infoscience.epfl.ch:279357","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/279357","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"research article"}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:279357","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/279357","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"research article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4830013026","display_name":null,"funder_award_id":"NRF-2018M3E3A1057289","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320321365","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":92,"referenced_works":["https://openalex.org/W86140595","https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1909316225","https://openalex.org/W1963882359","https://openalex.org/W1965572510","https://openalex.org/W1986266272","https://openalex.org/W2005876512","https://openalex.org/W2113569611","https://openalex.org/W2119535410","https://openalex.org/W2121396509","https://openalex.org/W2121927366","https://openalex.org/W2128254161","https://openalex.org/W2154621477","https://openalex.org/W2163146621","https://openalex.org/W2194775991","https://openalex.org/W2209874411","https://openalex.org/W2308529009","https://openalex.org/W2414711238","https://openalex.org/W2466666260","https://openalex.org/W2509784253","https://openalex.org/W2520707372","https://openalex.org/W2559264300","https://openalex.org/W2559918205","https://openalex.org/W2563705555","https://openalex.org/W2580458810","https://openalex.org/W2609883120","https://openalex.org/W2613034492","https://openalex.org/W2620629206","https://openalex.org/W2737207197","https://openalex.org/W2740982616","https://openalex.org/W2748263833","https://openalex.org/W2777170053","https://openalex.org/W2778532031","https://openalex.org/W2780930362","https://openalex.org/W2789288870","https://openalex.org/W2792892164","https://openalex.org/W2798401637","https://openalex.org/W2798744505","https://openalex.org/W2857642368","https://openalex.org/W2884068670","https://openalex.org/W2887181327","https://openalex.org/W2891279733","https://openalex.org/W2893221507","https://openalex.org/W2895013824","https://openalex.org/W2896911342","https://openalex.org/W2910832120","https://openalex.org/W2912435603","https://openalex.org/W2913360047","https://openalex.org/W2918626955","https://openalex.org/W2930755307","https://openalex.org/W2951019013","https://openalex.org/W2953133772","https://openalex.org/W2954171777","https://openalex.org/W2954787828","https://openalex.org/W2958407526","https://openalex.org/W2962793481","https://openalex.org/W2963017889","https://openalex.org/W2963073614","https://openalex.org/W2963426332","https://openalex.org/W2963588298","https://openalex.org/W2963730200","https://openalex.org/W2963843230","https://openalex.org/W2963866045","https://openalex.org/W2963878020","https://openalex.org/W2964121744","https://openalex.org/W2964212750","https://openalex.org/W2964248098","https://openalex.org/W2964267765","https://openalex.org/W2967584026","https://openalex.org/W2970842755","https://openalex.org/W2980047233","https://openalex.org/W3098038213","https://openalex.org/W3104533206","https://openalex.org/W3159245327","https://openalex.org/W4297692481","https://openalex.org/W6620707391","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6716109767","https://openalex.org/W6719936175","https://openalex.org/W6730052861","https://openalex.org/W6732779862","https://openalex.org/W6747084010","https://openalex.org/W6749443224","https://openalex.org/W6753478222","https://openalex.org/W6754958047","https://openalex.org/W6755406125"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W4293226380","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2080152487","https://openalex.org/W2239445980","https://openalex.org/W2995553446","https://openalex.org/W2120455979"],"abstract_inverted_index":{"Leveraging":[0],"on":[1,54,213],"recent":[2],"advances":[3],"in":[4,91],"deep":[5],"convolutional":[6],"neural":[7],"networks":[8,84,115],"(CNNs),":[9],"single":[10,69],"image":[11,70,80,140,148],"deraining":[12,31,71,83,114],"has":[13,233],"been":[14,234],"studied":[15],"as":[16,243],"a":[17,40,50,64,107,178,190,244],"learning":[18,36,66],"task,":[19],"achieving":[20],"an":[21,145],"outstanding":[22],"performance":[23],"over":[24],"traditional":[25],"hand-designed":[26],"approaches.":[27],"Current":[28],"CNNs":[29],"based":[30],"approaches":[32],"adopt":[33],"the":[34,78,88,113,118,123,132,138,150,155,158,207,224,237],"supervised":[35],"framework":[37,67],"that":[38,72,112,136,157,182,206,236],"uses":[39],"massive":[41],"training":[42],"data":[43],"generated":[44],"with":[45,144],"synthetic":[46,79,214],"rain":[47,102,160,174,202],"streaks,":[48],"having":[49],"limited":[51],"generalization":[52],"ability":[53],"real":[55,196,216],"rainy":[56,147,198,217,230],"images.":[57],"To":[58,171],"address":[59],"this":[60],"problem,":[61],"we":[62,105,176],"propose":[63],"novel":[65,191],"for":[68,100,247],"leverages":[73],"time-lapse":[74,89,124,193],"sequences":[75,90],"instead":[76],"of":[77],"pairs.":[81],"The":[82],"are":[85,97,162],"trained":[86],"using":[87,154],"which":[92],"both":[93,219],"camera":[94],"and":[95,149,167,215,221],"scenes":[96],"static":[98],"except":[99],"time-varying":[101],"streaks.":[103],"Specifically,":[104],"formulate":[106],"background":[108],"consistency":[109],"loss":[110,130,135,153],"such":[111],"consistently":[116],"generate":[117],"same":[119],"derained":[120,139],"images":[121,199,218],"from":[122],"sequences.":[125],"We":[126,187],"additionally":[127],"introduce":[128],"two":[129],"functions,":[131],"structure":[133],"similarity":[134],"encourages":[137],"to":[141,164],"be":[142,165,241],"similar":[143],"input":[146],"directional":[151],"gradient":[152],"assumption":[156],"estimated":[159],"streaks":[161],"likely":[163],"sparse":[166],"have":[168],"dominant":[169],"directions.":[170],"consider":[172],"various":[173,201],"conditions,":[175,231],"leverage":[177],"dynamic":[179],"fusion":[180],"module":[181],"effectively":[183],"fuses":[184],"multi-scale":[185],"features.":[186],"also":[188],"build":[189],"large-scale":[192],"dataset":[194],"providing":[195],"world":[197],"containing":[200],"conditions.":[203],"Experiments":[204],"demonstrate":[205],"proposed":[208,238],"method":[209,239],"outperforms":[210],"state-of-the-art":[211],"techniques":[212],"qualitatively":[220],"quantitatively.":[222],"On":[223],"high-level":[225],"vision":[226],"tasks":[227],"under":[228],"severe":[229],"it":[232],"shown":[235],"can":[240],"utilized":[242],"pre-preprocessing":[245],"step":[246],"subsequent":[248],"tasks.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
