{"id":"https://openalex.org/W4402402238","doi":"https://doi.org/10.1109/mapr63514.2024.10660776","title":"Contrastive Learning with Weakly Pair Images for Traffic Image Deraining","display_name":"Contrastive Learning with Weakly Pair Images for Traffic Image Deraining","publication_year":2024,"publication_date":"2024-08-15","ids":{"openalex":"https://openalex.org/W4402402238","doi":"https://doi.org/10.1109/mapr63514.2024.10660776"},"language":"en","primary_location":{"id":"doi:10.1109/mapr63514.2024.10660776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mapr63514.2024.10660776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","raw_type":"proceedings-article"},"type":"conference-paper","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":null,"display_name":"Quang Minh Tran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quang Minh Tran","raw_affiliation_strings":["University of Information Technology,Ho Chi Minh City,Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Information Technology,Ho Chi Minh City,Vietnam","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081841048","display_name":"Thanh Duc Ngo","orcid":"https://orcid.org/0000-0001-6882-0070"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thanh Duc Ngo","raw_affiliation_strings":["University of Information Technology,Ho Chi Minh City,Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Information Technology,Ho Chi Minh City,Vietnam","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113502919","display_name":"Tien-Dung Mai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tien-Dung Mai","raw_affiliation_strings":["University of Information Technology,Ho Chi Minh City,Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Information Technology,Ho Chi Minh City,Vietnam","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2629,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53735027,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9994000196456909,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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":0.6448438763618469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6045671701431274},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49615177512168884},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4459786117076874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37616580724716187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6448438763618469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6045671701431274},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49615177512168884},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4459786117076874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37616580724716187}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mapr63514.2024.10660776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mapr63514.2024.10660776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2740982616","https://openalex.org/W2898337423","https://openalex.org/W3034242291","https://openalex.org/W3108316907","https://openalex.org/W3158248812","https://openalex.org/W3171125843","https://openalex.org/W3173269149","https://openalex.org/W3183026600","https://openalex.org/W4224922575","https://openalex.org/W4225672218","https://openalex.org/W4226134400","https://openalex.org/W4304083162","https://openalex.org/W4312295033","https://openalex.org/W4312399981","https://openalex.org/W4312425087","https://openalex.org/W4312460946","https://openalex.org/W4312723380","https://openalex.org/W4362703401","https://openalex.org/W4380053099","https://openalex.org/W4402715864","https://openalex.org/W6862041540"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Image":[0],"deraining":[1,25,112,123],"is":[2,48,100,119],"an":[3],"image":[4,13],"restoration":[5],"task":[6],"that":[7,39,132],"aims":[8],"at":[9],"decomposing":[10],"a":[11,77,110],"rainy":[12],"into":[14],"the":[15,20,37,40,49,96,120,126,147],"clear":[16],"scene":[17],"layer":[18],"and":[19,30,45,60],"rain":[21,44,50],"layer.":[22],"Most":[23],"existing":[24,140],"methods":[26,141],"use":[27],"supervised":[28],"learning":[29,82],"training":[31],"on":[32,84],"synthetic":[33],"rainy-clear":[34],"pairs":[35],"under":[36],"assumption":[38,64],"only":[41,102],"difference":[42,97],"between":[43,98],"non-rain":[46],"images":[47,99],"effect.":[51],"Since":[52],"scenes":[53],"constantly":[54],"change":[55],"due":[56],"to":[57,69],"vehicle":[58],"movement":[59],"other":[61,139],"activities,":[62],"this":[63,73],"nearly":[65],"fails":[66],"when":[67],"applied":[68],"traffic":[70,115,127],"data.":[71],"In":[72,106],"work,":[74],"we":[75,108],"introduce":[76],"de-raining":[78],"framework":[79,89],"using":[80],"contrastive":[81],"based":[83],"Vision":[85],"Transformer.":[86],"The":[87,129],"proposed":[88],"utilizes":[90],"weakly":[91],"paired":[92],"images,":[93],"in":[94,125,146],"which":[95],"not":[101],"caused":[103],"by":[104],"rain.":[105],"addition,":[107],"collect":[109],"real-world":[111,122],"dataset":[113,124],"from":[114],"surveillance":[116],"cameras.":[117],"This":[118],"first":[121],"domain.":[128],"experiments":[130],"show":[131],"our":[133],"method":[134],"achieves":[135],"competitive":[136],"performance":[137],"with":[138],"while":[142],"taking":[143],"less":[144],"time":[145],"inference":[148],"process.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
