{"id":"https://openalex.org/W7140232650","doi":"https://doi.org/10.48550/arxiv.2603.21661","title":"Cross-Scenario Deraining Adaptation with Unpaired Data: Superpixel Structural Priors and Multi-Stage Pseudo-Rain Synthesis","display_name":"Cross-Scenario Deraining Adaptation with Unpaired Data: Superpixel Structural Priors and Multi-Stage Pseudo-Rain Synthesis","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140232650","doi":"https://doi.org/10.48550/arxiv.2603.21661"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.21661","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21661","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.21661","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhao, Kangbo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Kangbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Guan, Miaoxin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Miaoxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Chen, Xiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shi, Yukai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Yukai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Pan, Jinshan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jinshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.993399977684021,"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":0.993399977684021,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.00039999998989515007,"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/prior-probability","display_name":"Prior probability","score":0.6847000122070312},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6305000185966492},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5777999758720398},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5745000243186951},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4577000141143799},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41019999980926514},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36739999055862427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7228000164031982},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6847000122070312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6582000255584717},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6305000185966492},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5777999758720398},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5745000243186951},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4577000141143799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3711000084877014},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3391999900341034},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.21661","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21661","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.21661","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.21661","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Image":[0],"deraining":[1,79,182],"plays":[2],"a":[3,12,76,106,126,154,172],"pivotal":[4],"role":[5],"in":[6,30,95,203],"low-level":[7],"computer":[8],"vision,":[9],"serving":[10],"as":[11,171],"prerequisite":[13],"for":[14,91],"robust":[15],"outdoor":[16],"surveillance":[17],"and":[18,61,148],"autonomous":[19],"driving":[20],"systems.":[21],"While":[22],"deep":[23],"learning":[24],"paradigms":[25],"have":[26],"achieved":[27],"remarkable":[28,194],"success":[29],"firmly":[31],"aligned":[32],"settings,":[33],"they":[34],"often":[35],"suffer":[36],"from":[37,52,83,116],"severe":[38],"performance":[39],"degradation":[40],"when":[41],"generalized":[42],"to":[43,111,132,163,199,201],"unseen":[44],"Out-of-Distribution":[45],"(OOD)":[46],"scenarios.":[47],"This":[48,168],"failure":[49],"stems":[50],"primarily":[51],"the":[53,62,89,96,117,144],"significant":[54],"domain":[55,119],"discrepancy":[56],"between":[57],"synthetic":[58],"training":[59,209],"datasets":[60],"complex":[63],"physical":[64],"dynamics":[65],"of":[66,146,177,197],"real-world":[67],"rain.":[68],"To":[69],"address":[70],"these":[71,134],"challenges,":[72],"this":[73],"paper":[74],"proposes":[75],"pioneering":[77],"cross-scenario":[78],"adaptation":[80],"framework.":[81],"Diverging":[82],"conventional":[84],"approaches,":[85],"our":[86,191],"method":[87],"obviates":[88],"requirements":[90],"paired":[92],"rainy":[93],"observations":[94],"target":[97,138],"domain,":[98],"leveraging":[99],"exclusively":[100],"rain-free":[101],"background":[102],"images.":[103],"We":[104],"design":[105],"Superpixel":[107],"Generation":[108],"(Sup-Gen)":[109],"module":[110,175],"extract":[112],"stable":[113],"structural":[114],"priors":[115],"source":[118,135],"using":[120],"Simple":[121],"Linear":[122],"Iterative":[123],"Clustering.":[124],"Subsequently,":[125],"Resolution-adaptive":[127],"Fusion":[128],"strategy":[129],"is":[130],"introduced":[131],"align":[133],"structures":[136],"with":[137],"backgrounds":[139],"through":[140],"texture":[141],"similarity,":[142],"ensuring":[143],"synthesis":[145],"diverse":[147],"realistic":[149,165],"pseudo-data.":[150],"Finally,":[151],"we":[152],"implement":[153],"pseudo-label":[155],"re-Synthesize":[156],"mechanism":[157],"that":[158,190],"employs":[159],"multi-stage":[160],"noise":[161],"generation":[162],"simulate":[164],"rain":[166],"streaks.":[167],"framework":[169],"functions":[170],"versatile":[173],"plug-and-play":[174],"capable":[176],"seamless":[178],"integration":[179],"into":[180],"arbitrary":[181],"architectures.":[183],"Extensive":[184],"experiments":[185],"on":[186],"state-of-the-art":[187],"models":[188],"demonstrate":[189],"approach":[192],"yields":[193],"PSNR":[195],"gains":[196],"up":[198],"32%":[200],"59%":[202],"OOD":[204],"domains":[205],"while":[206],"significantly":[207],"accelerating":[208],"convergence.":[210]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-25T00:00:00"}
