{"id":"https://openalex.org/W3206107421","doi":"https://doi.org/10.1109/lsp.2021.3120598","title":"Reconciling Hand-Crafted and Self-Supervised Deep Priors for Video Directional Rain Streaks Removal","display_name":"Reconciling Hand-Crafted and Self-Supervised Deep Priors for Video Directional Rain Streaks Removal","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3206107421","doi":"https://doi.org/10.1109/lsp.2021.3120598","mag":"3206107421"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2021.3120598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3120598","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-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/A5110808792","display_name":"Junhao Zhuang","orcid":"https://orcid.org/0000-0002-1642-0750"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun-Hao Zhuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037421955","display_name":"Yisi Luo","orcid":"https://orcid.org/0000-0001-9295-4896"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi-Si Luo","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9295-4896","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011715660","display_name":"Xi-Le Zhao","orcid":"https://orcid.org/0000-0002-6540-946X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xi-Le Zhao","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6540-946X","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036399063","display_name":"Tai-Xiang Jiang","orcid":"https://orcid.org/0000-0002-9099-4154"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tai-Xiang Jiang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9099-4154","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5653,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.68264457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"28","issue":null,"first_page":"2147","last_page":"2151"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9889000058174133,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6963351368904114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6813806891441345},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6672564744949341},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5962956547737122},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4732910990715027},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.18206480145454407}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6963351368904114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6813806891441345},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6672564744949341},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5962956547737122},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4732910990715027},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.18206480145454407}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2021.3120598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3120598","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5199999809265137,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1090016836","display_name":null,"funder_award_id":"JBK2102001","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G1810718286","display_name":null,"funder_award_id":"12001446","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3778334585","display_name":null,"funder_award_id":"12171072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7305357247","display_name":null,"funder_award_id":"2020YFA0714001","funder_id":"https://openalex.org/F4320336026","funder_display_name":"National Key Research and Development Program of China Stem Cell and Translational Research"},{"id":"https://openalex.org/G8330053271","display_name":null,"funder_award_id":"61876203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320336026","display_name":"National Key Research and Development Program of China Stem Cell and Translational Research","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1909316225","https://openalex.org/W2117406282","https://openalex.org/W2209874411","https://openalex.org/W2466666260","https://openalex.org/W2509784253","https://openalex.org/W2559264300","https://openalex.org/W2737207197","https://openalex.org/W2740982616","https://openalex.org/W2753548330","https://openalex.org/W2777170053","https://openalex.org/W2777241530","https://openalex.org/W2789288870","https://openalex.org/W2790883954","https://openalex.org/W2798401637","https://openalex.org/W2798744505","https://openalex.org/W2888632407","https://openalex.org/W2889656958","https://openalex.org/W2906196996","https://openalex.org/W2912435603","https://openalex.org/W2956718304","https://openalex.org/W2963843230","https://openalex.org/W2964013315","https://openalex.org/W2964121744","https://openalex.org/W2964212750","https://openalex.org/W2964267765","https://openalex.org/W2965958849","https://openalex.org/W2970517192","https://openalex.org/W2980047233","https://openalex.org/W3028045870","https://openalex.org/W3035250394","https://openalex.org/W3035688623","https://openalex.org/W3098038213","https://openalex.org/W3176958085","https://openalex.org/W3198251760","https://openalex.org/W3201640799","https://openalex.org/W6631190155","https://openalex.org/W6779941567","https://openalex.org/W6791650622"],"related_works":["https://openalex.org/W1891287906","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W2755342338","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2058170566"],"abstract_inverted_index":{"Removing":[0],"rain":[1,34,110],"streaks":[2,35,111],"in":[3,112],"videos":[4],"has":[5],"recently":[6],"received":[7],"much":[8],"attention.":[9],"Existing":[10],"hand-crafted":[11,40,46],"priors-based":[12],"methods":[13,23],"suffer":[14],"from":[15],"limited":[16],"representation":[17,101],"abilities,":[18],"and":[19,41,56,90,100],"supervised":[20],"deep":[21,43,64,74,92],"learning":[22],"need":[24],"high-quality":[25],"training":[26,82],"data.":[27,83],"This":[28],"paper":[29],"proposes":[30],"a":[31,63],"novel":[32],"video":[33,79],"removal":[36],"method":[37,85,105,127,136],"by":[38],"reconciling":[39],"self-supervised":[42,91],"priors.":[44],"The":[45],"priors":[47,89,93],"include":[48],"the":[49,53,57,73,77,118,132],"learned":[50],"gradient":[51],"prior,":[52,55],"sparse":[54],"temporal":[58],"local":[59],"smooth":[60],"prior.":[61],"Meanwhile,":[62],"convolutional":[65],"neural":[66],"network":[67],"is":[68],"employed":[69],"to":[70,94],"self-supervisedly":[71],"capture":[72],"prior":[75],"of":[76,134],"clean":[78],"without":[80],"any":[81],"Our":[84],"organically":[86],"integrates":[87],"hand-crated":[88],"achieve":[95],"both":[96],"high":[97],"generalization":[98],"abilities":[99],"abilities.":[102],"Thus,":[103],"our":[104,135],"can":[106],"faithfully":[107],"remove":[108],"directional":[109],"real":[113],"world":[114],"videos.":[115],"To":[116],"address":[117],"resulting":[119],"model,":[120],"we":[121],"introduce":[122],"an":[123],"alternating":[124],"direction":[125],"multiplier":[126],"algorithm.":[128],"Extensive":[129],"experiments":[130],"validate":[131],"superiority":[133],"over":[137],"state-of-the-art":[138],"methods.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
