{"id":"https://openalex.org/W7116838078","doi":"https://doi.org/10.1109/tip.2025.3645599","title":"Unlocking Cross-Domain Synergies for Domain Adaptive Semantic Segmentation","display_name":"Unlocking Cross-Domain Synergies for Domain Adaptive Semantic Segmentation","publication_year":2025,"publication_date":"2025-12-23","ids":{"openalex":"https://openalex.org/W7116838078","doi":"https://doi.org/10.1109/tip.2025.3645599","pmid":"https://pubmed.ncbi.nlm.nih.gov/41433171"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2025.3645599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3645599","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","pubmed"],"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/A5121032914","display_name":"Qin Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qin Xu","raw_affiliation_strings":["Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055030063","display_name":"Qihang Wu","orcid":"https://orcid.org/0000-0002-4228-3286"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qihang Wu","raw_affiliation_strings":["Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121026168","display_name":"Bo Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Jiang","raw_affiliation_strings":["Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121094798","display_name":"Jiahui Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Wang","raw_affiliation_strings":["Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400907","display_name":"Yuan Chen","orcid":"https://orcid.org/0009-0008-7270-7669"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Chen","raw_affiliation_strings":["School of Internet, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Internet, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5098121783","display_name":"JinHui TANG","orcid":null},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["College of Information Science and Technology and Artificial Intelligence, Nanjing Forestry University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology and Artificial Intelligence, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5121032914"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.81338828,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"136","last_page":"149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10028","display_name":"Topic Modeling","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0010000000474974513,"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/discriminative-model","display_name":"Discriminative model","score":0.715499997138977},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6317999958992004},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6164000034332275},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.6132000088691711},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5722000002861023},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5013999938964844},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4934000074863434},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.43700000643730164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8044999837875366},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.715499997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6794999837875366},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6317999958992004},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6164000034332275},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.6132000088691711},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5013999938964844},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4934000074863434},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.43700000643730164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4309999942779541},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.359499990940094},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2809999883174896},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2506999969482422},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2025.3645599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3645599","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":"pmid:41433171","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41433171","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7025678753852844,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W2125865219","https://openalex.org/W2138621090","https://openalex.org/W2340897893","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2962687275","https://openalex.org/W2963107255","https://openalex.org/W2969893028","https://openalex.org/W2972285644","https://openalex.org/W2980113592","https://openalex.org/W2981429991","https://openalex.org/W2985406498","https://openalex.org/W2985409929","https://openalex.org/W2998607115","https://openalex.org/W3000172657","https://openalex.org/W3034417116","https://openalex.org/W3034562924","https://openalex.org/W3035160371","https://openalex.org/W3035294798","https://openalex.org/W3102977943","https://openalex.org/W3107590933","https://openalex.org/W3108566666","https://openalex.org/W3110486195","https://openalex.org/W3119635706","https://openalex.org/W3120562181","https://openalex.org/W3120804725","https://openalex.org/W3157653192","https://openalex.org/W3161810785","https://openalex.org/W3164066238","https://openalex.org/W3168822201","https://openalex.org/W3175294391","https://openalex.org/W3175308890","https://openalex.org/W3195892675","https://openalex.org/W3202115483","https://openalex.org/W3215041655","https://openalex.org/W3217147624","https://openalex.org/W4225649887","https://openalex.org/W4287124998","https://openalex.org/W4291961281","https://openalex.org/W4295788754","https://openalex.org/W4312768455","https://openalex.org/W4317038436","https://openalex.org/W4319301015","https://openalex.org/W4321608048","https://openalex.org/W4376852271","https://openalex.org/W4382465753","https://openalex.org/W4386047746","https://openalex.org/W4386065590","https://openalex.org/W4386075540","https://openalex.org/W4386075777","https://openalex.org/W4386076377","https://openalex.org/W4387967997","https://openalex.org/W4388186252","https://openalex.org/W4388191728","https://openalex.org/W4390871827","https://openalex.org/W4390871899","https://openalex.org/W4390872416","https://openalex.org/W4390872645","https://openalex.org/W4390874217","https://openalex.org/W4393153135","https://openalex.org/W4394593077","https://openalex.org/W4398226180","https://openalex.org/W4403068466","https://openalex.org/W4403843485","https://openalex.org/W4404435992","https://openalex.org/W4408146232"],"related_works":[],"abstract_inverted_index":{"Unsupervised":[0],"domain":[1,15,81,107],"adaptation":[2,82],"semantic":[3,83,204],"segmentation":[4],"(UDASS)":[5],"aims":[6],"to":[7,52],"perform":[8],"dense":[9],"prediction":[10],"on":[11,20,41,202,223],"the":[12,18,54,58,62,92,118,130,135,146,152,170,177,196,203,211,229,232,238],"unlabeled":[13],"target":[14,63,131,199],"by":[16],"training":[17,43,115],"model":[19],"a":[21,76,97,123,140],"labeled":[22],"source":[23,65,106,153,197],"domain.":[24,132],"In":[25],"this":[26,69,72],"field,":[27],"self-training":[28],"approaches":[29],"have":[30],"demonstrated":[31],"strong":[32],"competitiveness":[33],"and":[34,64,109,148,155,163,175,192,198,243],"advantages.":[35],"However,":[36],"existing":[37,119,218],"methods":[38],"often":[39],"rely":[40],"additional":[42,114],"data":[44],"(such":[45],"as":[46],"reference":[47],"datasets":[48,227],"or":[49],"depth":[50],"maps)":[51],"rectify":[53],"unreliable":[55,149],"pseudo-labels,":[56,137],"ignoring":[57],"cross-domain":[59,157],"interaction":[60],"between":[61],"domains.":[66],"To":[67,133,168],"address":[68],"issue,":[70],"in":[71,91,195,217,235],"paper,":[73],"we":[74,95,138,182],"propose":[75,183],"novel":[77],"method":[78,128],"for":[79,129],"unsupervised":[80],"segmentation,":[84],"termed":[85],"Unlocking":[86],"Cross-Domain":[87],"Synergies":[88],"(UCDS).":[89],"Specifically,":[90],"UCDS":[93,234],"network,":[94],"design":[96,139],"new":[98],"Dynamic":[99,124],"Self-Correction":[100,162],"(DSC)":[101],"module":[102],"that":[103,144],"effectively":[104,209],"transfers":[105],"knowledge":[108],"generates":[110],"high-confidence":[111],"pseudo-labels":[112],"without":[113],"resources.":[116],"Unlike":[117],"methods,":[120],"DSC":[121],"proposes":[122],"Noisy":[125],"Label":[126],"Detection":[127],"correct":[134],"noisy":[136],"Dual":[141],"Bank":[142],"mechanism":[143],"explores":[145],"reliable":[147],"predictions":[150],"of":[151,173,179,231],"domain,":[154],"conducts":[156],"synergy":[158],"through":[159],"Weighted":[160],"Reassignment":[161],"Negative":[164],"Correction":[165],"Prevention":[166],"strategies.":[167],"enhance":[169],"discriminative":[171],"ability":[172],"features":[174],"amplify":[176],"dissimilarity":[178],"different":[180,207],"categories,":[181,208],"Discrepancy-based":[184],"Contrastive":[185],"Learning":[186],"(DCL).":[187],"The":[188,241],"DCL":[189],"selects":[190],"positive":[191],"negative":[193,214],"samples":[194,215],"domains":[200],"based":[201],"discrepancies":[205],"among":[206],"avoiding":[210],"numerous":[212],"false":[213],"found":[216],"methods.":[219,240],"Extensive":[220],"experimental":[221],"results":[222],"three":[224],"commonly":[225],"used":[226],"demonstrate":[228],"superiority":[230],"proposed":[233],"comparison":[236],"with":[237],"state-of-the-art":[239],"project":[242],"code":[244],"are":[245],"available":[246],"at":[247],"https://github.com/wqh011128/UCDS.":[248]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-23T00:00:00"}
