{"id":"https://openalex.org/W7084936429","doi":"https://doi.org/10.1109/tmm.2025.3618579","title":"MFJLN: Multi-Frequency Feature Joint Learning Network for Rain Removal","display_name":"MFJLN: Multi-Frequency Feature Joint Learning Network for Rain Removal","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7084936429","doi":"https://doi.org/10.1109/tmm.2025.3618579"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3618579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618579","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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":null,"display_name":"Yong Yang","orcid":"https://orcid.org/0000-0001-9467-0942"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Yang","raw_affiliation_strings":["School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-9467-0942","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiaxuan Yang","orcid":"https://orcid.org/0009-0004-6558-4198"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxuan Yang","raw_affiliation_strings":["School of Computer Science and Technology, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0004-6558-4198","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuying Huang","orcid":"https://orcid.org/0000-0003-2771-8461"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuying Huang","raw_affiliation_strings":["School of Software, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2771-8461","affiliations":[{"raw_affiliation_string":"School of Software, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":null,"display_name":"Weiguo Wan","orcid":"https://orcid.org/0000-0002-3537-979X"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiguo Wan","raw_affiliation_strings":["School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0002-3537-979X","affiliations":[{"raw_affiliation_string":"School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, China","institution_ids":["https://openalex.org/I59649739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61391353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"9632","last_page":"9645"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10373","display_name":"Renal Transplantation Outcomes and Treatments","score":0.8582000136375427,"subfield":{"id":"https://openalex.org/subfields/2747","display_name":"Transplantation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10373","display_name":"Renal Transplantation Outcomes and Treatments","score":0.8582000136375427,"subfield":{"id":"https://openalex.org/subfields/2747","display_name":"Transplantation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10291","display_name":"Dialysis and Renal Disease Management","score":0.0681999996304512,"subfield":{"id":"https://openalex.org/subfields/2727","display_name":"Nephrology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10804","display_name":"Health Systems, Economic Evaluations, Quality of Life","score":0.015699999406933784,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.635699987411499},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6319000124931335},{"id":"https://openalex.org/keywords/streak","display_name":"Streak","score":0.6177999973297119},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.608299970626831},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5879999995231628},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5863000154495239},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5196999907493591},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4860999882221222},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.47679999470710754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7791000008583069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.654699981212616},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.635699987411499},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6319000124931335},{"id":"https://openalex.org/C65185188","wikidata":"https://www.wikidata.org/wiki/Q107775","display_name":"Streak","level":2,"score":0.6177999973297119},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.608299970626831},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5879999995231628},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5863000154495239},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4959999918937683},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4860999882221222},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.47679999470710754},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4027000069618225},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.36059999465942383},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.34310001134872437},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2773999869823456},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.26759999990463257}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3618579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618579","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.6376949548721313,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G1646045178","display_name":null,"funder_award_id":"24JCZDJC00130","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G6245653521","display_name":"\u8054\u5408\u7a7a\u95f4-\u5149\u8c31\u7279\u5f81\u7684\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u9065\u611f\u56fe\u50cf\u8d85\u5206\u878d\u5408\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"62072218","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7398622622","display_name":null,"funder_award_id":"25JCZDJC00540","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G7956009394","display_name":null,"funder_award_id":"62261025","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/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W2114770744","https://openalex.org/W2121396509","https://openalex.org/W2133665775","https://openalex.org/W2154621477","https://openalex.org/W2209874411","https://openalex.org/W2466666260","https://openalex.org/W2509784253","https://openalex.org/W2559264300","https://openalex.org/W2560023338","https://openalex.org/W2777170053","https://openalex.org/W2780930362","https://openalex.org/W2884068670","https://openalex.org/W2887181327","https://openalex.org/W2912435603","https://openalex.org/W2913360047","https://openalex.org/W2930755307","https://openalex.org/W2963037989","https://openalex.org/W2964101377","https://openalex.org/W2964212750","https://openalex.org/W2976715267","https://openalex.org/W3017109268","https://openalex.org/W3035250394","https://openalex.org/W3035326127","https://openalex.org/W3035564946","https://openalex.org/W3081770448","https://openalex.org/W3097096317","https://openalex.org/W3100618669","https://openalex.org/W3138516171","https://openalex.org/W3140957206","https://openalex.org/W3170697543","https://openalex.org/W3174756006","https://openalex.org/W3186182384","https://openalex.org/W3201952986","https://openalex.org/W3212876649","https://openalex.org/W4225672218","https://openalex.org/W4226078259","https://openalex.org/W4230654051","https://openalex.org/W4283023197","https://openalex.org/W4312526798","https://openalex.org/W4312812783","https://openalex.org/W4318953193","https://openalex.org/W4319300170","https://openalex.org/W4321021768","https://openalex.org/W4321435343","https://openalex.org/W4376456845","https://openalex.org/W4382239987","https://openalex.org/W4382449856","https://openalex.org/W4385245566","https://openalex.org/W4386047745","https://openalex.org/W4386075800","https://openalex.org/W4392824670","https://openalex.org/W4402904229","https://openalex.org/W4408935015"],"related_works":[],"abstract_inverted_index":{"Most":[0],"deep":[1],"learning-based":[2],"rain":[3,7,23,38,46,50,116,135,228,246],"removal":[4,36,51,229],"methods":[5,230],"consider":[6],"streaks":[8,47,117,247],"as":[9,68],"a":[10,57,69,76,82,90,95,124,154,180],"part":[11],"of":[12,32,37,89,177,198,233],"the":[13,17,30,49,110,151,175,189,196],"high-frequency":[14,122,146],"information":[15],"in":[16,48,121,150,231],"image":[18],"to":[19,29,41,101,132,168,187,224],"extract":[20,133],"and":[21,75,94,145,214,236,256],"remove":[22,245,254],"streak":[24,136],"features.":[25,172],"This":[26],"usually":[27],"leads":[28],"problem":[31],"excessive":[33],"or":[34,44],"insufficient":[35],"streaks,":[39],"leading":[40],"blurred":[42],"edges":[43],"residual":[45],"results.":[52],"To":[53,173],"resolve":[54],"this":[55],"problem,":[56],"multi-frequency":[58],"feature":[59,84,104,126,181,206],"joint":[60],"learning":[61],"network":[62],"(MFJLN)is":[63],"proposed,":[64],"which":[65],"is":[66,99,130,159,185,222],"constructed":[67,100,131,186],"U-shaped":[70],"structure":[71],"including":[72],"an":[73,163],"encoder":[74],"decoder.":[77],"At":[78],"each":[79,199],"scale":[80],"layer,":[81,153],"full-frequency":[83],"fusion":[85,182],"module":[86],"(3FM)":[87],"consisting":[88],"spatial":[91,111],"domain":[92,97,112],"branch":[93,98],"frequency":[96,140],"achieve":[102,174],"accurate":[103,170],"extraction":[105,127],"at":[106],"different":[107],"scales.":[108],"In":[109,148,239],"branch,":[113],"considering":[114],"that":[115,219],"not":[118,243],"only":[119,244],"exist":[120],"components,":[123],"multifrequency":[125],"block":[128,157,183],"(MFEB)":[129],"rich":[134],"features":[137,190,197],"from":[138,191,248],"multiple":[139],"layers,":[141],"namely":[142],"low-frequency,":[143],"mid-frequency,":[144],"layers.":[147],"addition,":[149,240],"low-frequency":[152],"masked":[155],"self-attention":[156],"(MSAB)":[158],"designed":[160],"by":[161],"defining":[162],"adaptive":[164],"position":[165],"weight":[166],"mask":[167],"learn":[169],"long-distance":[171],"reuse":[176],"encoding":[178,193],"features,":[179],"(FFB)":[184],"fuse":[188],"all":[192],"layers":[194],"with":[195],"decoding":[200],"layer":[201],"through":[202],"dense":[203],"links":[204],"for":[205],"reconstruction.":[207],"Numerous":[208],"experimental":[209],"results":[210],"on":[211],"both":[212],"synthetic":[213],"real-world":[215],"datasets":[216],"have":[217],"shown":[218],"our":[220],"MFJLN":[221,241],"superior":[223],"some":[225],"state-ofthe-art":[226],"(SOTA)":[227],"terms":[232],"visual":[234],"effects":[235],"quantitative":[237],"metrics.":[238],"can":[242],"rainy":[249],"images,":[250],"but":[251],"also":[252],"effectively":[253],"raindrops":[255],"snow":[257],"marks.":[258]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}