{"id":"https://openalex.org/W4417002760","doi":"https://doi.org/10.1109/tgrs.2025.3640112","title":"MASDG: Multiview Augmented Single-Source Domain Generalization Method for Robust Remote Sensing Building Extraction","display_name":"MASDG: Multiview Augmented Single-Source Domain Generalization Method for Robust Remote Sensing Building Extraction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4417002760","doi":"https://doi.org/10.1109/tgrs.2025.3640112"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3640112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3640112","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5075362060","display_name":"Yunjiao Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjiao Liu","raw_affiliation_strings":["School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100753233","display_name":"Yuanyuan Liu","orcid":"https://orcid.org/0000-0003-0465-3976"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Liu","raw_affiliation_strings":["School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-0465-3976","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114500391","display_name":"Kejun Liu","orcid":"https://orcid.org/0009-0008-2332-6157"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kejun Liu","raw_affiliation_strings":["School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0008-2332-6157","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuxuan Huang","orcid":"https://orcid.org/0009-0007-1094-934X"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Huang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0007-1094-934X","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033240507","display_name":"Chang Tang","orcid":"https://orcid.org/0000-0002-6515-7696"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Tang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-6515-7696","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076872319","display_name":"Wujie Zhou","orcid":"https://orcid.org/0000-0002-3055-2493"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wujie Zhou","raw_affiliation_strings":["Zhejiang University of Science and Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3055-2493","affiliations":[{"raw_affiliation_string":"Zhejiang University of Science and Technology, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457637","display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0001-5004-8975"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhe Chen","raw_affiliation_strings":["School of Computing, Engineering and Mathematical Sciences, and the Cisco-La Trobe Centre for Artificial Intelligence and Internet of Things, La Trobe University, Melbourne, VIC, Australia","School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Engineering and Mathematical Sciences, and the Cisco-La Trobe Centre for Artificial Intelligence and Internet of Things, La Trobe University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]},{"raw_affiliation_string":"School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389005","display_name":"Wei Xiang","orcid":"https://orcid.org/0000-0002-0608-065X"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wei Xiang","raw_affiliation_strings":["School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-0608-065X","affiliations":[{"raw_affiliation_string":"School of Computing, Engineering and Mathematical Sciences, La Trobe University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100385579","display_name":"Hongyan Zhang","orcid":"https://orcid.org/0000-0002-7894-5755"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Zhang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-7894-5755","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.188,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.94532795,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"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":0.5697000026702881,"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":0.5697000026702881,"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":0.21850000321865082,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.08630000054836273,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/feature-extraction","display_name":"Feature extraction","score":0.5472999811172485},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5217999815940857},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5041999816894531},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4715999960899353},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4677000045776367},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4327999949455261},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4189000129699707},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.41530001163482666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4147000014781952}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123000264167786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5620999932289124},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5217999815940857},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5041999816894531},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4677000045776367},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4327999949455261},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4147000014781952},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.39980000257492065},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39070001244544983},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3154999911785126},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.31279999017715454},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.301800012588501},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3640112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3640112","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1034316256","display_name":null,"funder_award_id":"2023AFB572","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G3057168972","display_name":null,"funder_award_id":"KLIGIP-2022-B10","funder_id":"https://openalex.org/F8678731271","funder_display_name":"Hubei Key Laboratory of Intelligent Geo-Information Processing"}],"funders":[{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null},{"id":"https://openalex.org/F8678731271","display_name":"Hubei Key Laboratory of Intelligent Geo-Information Processing","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1526448290","https://openalex.org/W2201792562","https://openalex.org/W2603777577","https://openalex.org/W2798658180","https://openalex.org/W2908320224","https://openalex.org/W2972285644","https://openalex.org/W2982206001","https://openalex.org/W3020349519","https://openalex.org/W3048159371","https://openalex.org/W3089265466","https://openalex.org/W3095799614","https://openalex.org/W3104369000","https://openalex.org/W3168588044","https://openalex.org/W3169545167","https://openalex.org/W3175956495","https://openalex.org/W3181515393","https://openalex.org/W3195722174","https://openalex.org/W4205138939","https://openalex.org/W4214480085","https://openalex.org/W4290712790","https://openalex.org/W4292793893","https://openalex.org/W4312243476","https://openalex.org/W4312521905","https://openalex.org/W4312815172","https://openalex.org/W4313045831","https://openalex.org/W4313067243","https://openalex.org/W4319663796","https://openalex.org/W4361801101","https://openalex.org/W4366331277","https://openalex.org/W4367171996","https://openalex.org/W4386065565","https://openalex.org/W4386076298","https://openalex.org/W4386598482","https://openalex.org/W4386634500","https://openalex.org/W4387704395","https://openalex.org/W4387967996","https://openalex.org/W4389890872","https://openalex.org/W4389990420","https://openalex.org/W4390871905","https://openalex.org/W4391454392","https://openalex.org/W4392739357","https://openalex.org/W4392980197","https://openalex.org/W4393150367","https://openalex.org/W4396241494","https://openalex.org/W4399039818","https://openalex.org/W4399206049","https://openalex.org/W4399526437","https://openalex.org/W4401327417","https://openalex.org/W4401635335","https://openalex.org/W4402259878","https://openalex.org/W4402265517","https://openalex.org/W4402727160","https://openalex.org/W4402727887","https://openalex.org/W4403737996","https://openalex.org/W4405967990","https://openalex.org/W4408048065"],"related_works":[],"abstract_inverted_index":{"Despite":[0],"advances":[1],"in":[2,35,68],"deep":[3],"learning":[4,206],"for":[5,96,160],"remote":[6],"sensing":[7],"building":[8,194],"extraction":[9],"(RSBE),":[10],"Multi-target":[11],"Domain":[12,81,123,128],"RSBE":[13],"(MD-RSBE)":[14],"remains":[15],"challenging,":[16],"as":[17],"it":[18],"requires":[19,52],"transferring":[20],"knowledge":[21],"from":[22,174,223],"a":[23,77,208,271],"labeled":[24],"source":[25,92,106,154],"domain":[26,33,41,88,107,140,199],"to":[27,61,149,191,246],"multiple":[28],"unlabeled":[29],"target":[30,94,260],"domains,":[31],"with":[32,170,257],"shifts":[34,89],"texture,":[36],"style,":[37],"and":[38,44,65,93,111,132,186,215],"semantics.":[39],"Existing":[40],"adaptation":[42],"(DA)":[43],"generalization":[45,67],"(DG)":[46],"methods":[47,269],"face":[48],"significant":[49,272],"limitations:":[50],"DA":[51],"target-domain":[53],"training,":[54,59],"while":[55,231],"DG":[56],"needs":[57],"multi-source":[58],"leading":[60],"high":[62],"training":[63],"costs":[64],"low":[66],"practical":[69],"MD-RSBE":[70,98,255],"scenarios.":[71],"To":[72,137],"address":[73],"this,":[74],"we":[75],"propose":[76],"Multi-view":[78],"Augmented":[79],"Single-source":[80],"Generalization":[82],"(MASDG)":[83],"method,":[84],"which":[85],"effectively":[86],"mitigates":[87],"across":[90,165,252],"RS":[91,167],"domains":[95,261],"robust":[97,248],"performance":[99],"by":[100,237,270],"enriching":[101],"the":[102,105,151,182,187,232],"diversity":[103,164],"of":[104,118,153],"through":[108],"multi-view":[109,193,212],"augmentation":[110],"enforcing":[112],"semantic":[113,216,235,244],"consistency.":[114],"Specifically,":[115],"MASDG":[116,265],"consists":[117],"three":[119,253],"key":[120],"components:":[121],"Texture-level":[122],"Augmentation":[124,129],"(TDA)":[125],"module,":[126],"Style-level":[127],"(SDA)":[130],"module":[131],"Semantic-invariant":[133],"Representation":[134],"Learning":[135],"(SRL).":[136],"mitigate":[138],"texture-level":[139],"shift,":[141],"TDA":[142],"first":[143],"introduces":[144],"parameter-optimized":[145],"multi-layer":[146],"random":[147],"convolution":[148],"modify":[150],"texture":[152,163],"image,":[155],"generating":[156],"texture-augmented":[157],"image":[158,172],"pairs":[159],"simulating":[161],"real-world":[162],"various":[166],"domains.":[168],"Then,":[169],"each":[171],"pair":[173],"TDA,":[175],"SDA":[176],"employs":[177],"two":[178],"paralleled":[179],"encoders,":[180],"namely":[181],"general":[183],"feature":[184,225],"encoder":[185],"batch-guided":[188],"style":[189],"encoder,":[190],"formulate":[192],"features,":[195],"further":[196],"mitigating":[197],"style-level":[198],"shift.":[200],"Finally,":[201],"SRL":[202],"ensures":[203],"semantic-invariant":[204],"representation":[205],"via":[207],"dual":[209],"mechanism,":[210],"including":[211],"segmentation":[213],"loss":[214],"consistency":[217],"loss.":[218],"The":[219],"former":[220],"generates":[221],"predictions":[222],"diverse":[224],"views":[226],"(original,":[227],"texture-augmented,":[228],"style-augmented,":[229],"etc.),":[230],"latter":[233],"performs":[234],"alignment":[236],"minimizing":[238],"distribution":[239],"discrepancies":[240],"among":[241],"predictions,":[242],"bridging":[243],"inconsistency":[245],"enable":[247],"segmentation.":[249],"Extensive":[250],"experiments":[251],"different":[254,259],"settings":[256],"7":[258],"demonstrate":[262],"that":[263],"our":[264],"outperforms":[266],"existing":[267],"state-of-the-art":[268],"margin.":[273]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-04T00:00:00"}
