{"id":"https://openalex.org/W4206782550","doi":"https://doi.org/10.1109/tits.2022.3140481","title":"Confidence-and-Refinement Adaptation Model for Cross-Domain Semantic Segmentation","display_name":"Confidence-and-Refinement Adaptation Model for Cross-Domain Semantic Segmentation","publication_year":2022,"publication_date":"2022-01-13","ids":{"openalex":"https://openalex.org/W4206782550","doi":"https://doi.org/10.1109/tits.2022.3140481"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3140481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3140481","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10147106/1/Confidence-and-Refinement_Adaptation_Model_for_Cross-Domain_Semantic_Segmentation.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100330121","display_name":"Xiaohong Zhang","orcid":"https://orcid.org/0000-0003-2320-0884"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohong Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073368817","display_name":"Yi Chen","orcid":"https://orcid.org/0000-0002-8762-4523"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Chen","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-8762-4523","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040995630","display_name":"Ziyi Shen","orcid":"https://orcid.org/0000-0001-6867-1909"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ziyi Shen","raw_affiliation_strings":["Department of Medical Physics and Biomedical Engineering, University College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0001-6867-1909","affiliations":[{"raw_affiliation_string":"Department of Medical Physics and Biomedical Engineering, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052917688","display_name":"Yuming Shen","orcid":"https://orcid.org/0000-0003-4017-9140"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuming Shen","raw_affiliation_strings":["Department of Engineering Science, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0003-4017-9140","affiliations":[{"raw_affiliation_string":"Department of Engineering Science, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064008061","display_name":"Haofeng Zhang","orcid":"https://orcid.org/0000-0002-4039-7618"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haofeng Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4039-7618","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100434437","display_name":"Yudong Zhang","orcid":"https://orcid.org/0000-0002-4870-1493"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yudong Zhang","raw_affiliation_strings":["School of Informatics, University of Leicester, Leicester, U.K"],"raw_orcid":"https://orcid.org/0000-0002-4870-1493","affiliations":[{"raw_affiliation_string":"School of Informatics, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3198,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.8940458,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"7","first_page":"9529","last_page":"9542"},"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":0.9993000030517578,"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":0.9993000030517578,"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":0.9987000226974487,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9933000206947327,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6456661820411682},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5804168581962585},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5464403629302979},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5361509323120117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5128555297851562},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41410961747169495},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3863055109977722},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3492567837238312},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15717840194702148},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.137015700340271},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.08525916934013367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6456661820411682},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5804168581962585},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5464403629302979},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5361509323120117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5128555297851562},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41410961747169495},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3863055109977722},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3492567837238312},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15717840194702148},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.137015700340271},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.08525916934013367},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tits.2022.3140481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3140481","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10147106","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10147106/","pdf_url":"https://discovery.ucl.ac.uk/10147106/1/Confidence-and-Refinement_Adaptation_Model_for_Cross-Domain_Semantic_Segmentation.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems (2022) (In press).","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10147106","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10147106/","pdf_url":"https://discovery.ucl.ac.uk/10147106/1/Confidence-and-Refinement_Adaptation_Model_for_Cross-Domain_Semantic_Segmentation.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems (2022) (In press).","raw_type":"Article"},"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4151098548","display_name":"\u9762\u5411\u590d\u6742\u591a\u89c6\u56fe\u56fe\u50cf\u7684\u9c81\u68d2\u5224\u522b\u8ddd\u79bb\u5ea6\u91cf\u534f\u540c\u5b66\u4e60\u7814\u7a76","funder_award_id":"62072246","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5371617261","display_name":"\u96f6\u6837\u672c\u5b66\u4e60\u4e2d\u7684\u8bed\u4e49\u5c5e\u6027\u8868\u793a\u53ca\u7279\u5f81\u5408\u6210\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61872187","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6911399322","display_name":null,"funder_award_id":"BK20201306","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G8952493281","display_name":null,"funder_award_id":"62077023","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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206782550.pdf","grobid_xml":"https://content.openalex.org/works/W4206782550.grobid-xml"},"referenced_works_count":94,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2214409633","https://openalex.org/W2279034837","https://openalex.org/W2306289963","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2431874326","https://openalex.org/W2475287302","https://openalex.org/W2487365028","https://openalex.org/W2560023338","https://openalex.org/W2562192638","https://openalex.org/W2630837129","https://openalex.org/W2775667105","https://openalex.org/W2787091153","https://openalex.org/W2895281799","https://openalex.org/W2944270177","https://openalex.org/W2962849264","https://openalex.org/W2962976523","https://openalex.org/W2963073217","https://openalex.org/W2963107255","https://openalex.org/W2963120918","https://openalex.org/W2963870446","https://openalex.org/W2963881378","https://openalex.org/W2963983207","https://openalex.org/W2964159141","https://openalex.org/W2964193438","https://openalex.org/W2969893028","https://openalex.org/W2970048031","https://openalex.org/W2972285644","https://openalex.org/W2980096013","https://openalex.org/W2981429991","https://openalex.org/W2981609437","https://openalex.org/W2981689412","https://openalex.org/W2982410491","https://openalex.org/W2985406498","https://openalex.org/W2985409929","https://openalex.org/W2986831462","https://openalex.org/W2997601829","https://openalex.org/W2998115938","https://openalex.org/W3023904705","https://openalex.org/W3034333089","https://openalex.org/W3034373787","https://openalex.org/W3034417116","https://openalex.org/W3034562924","https://openalex.org/W3035236545","https://openalex.org/W3035294798","https://openalex.org/W3035739565","https://openalex.org/W3082576756","https://openalex.org/W3092486982","https://openalex.org/W3096399234","https://openalex.org/W3098191145","https://openalex.org/W3101468328","https://openalex.org/W3102659010","https://openalex.org/W3102977943","https://openalex.org/W3106349512","https://openalex.org/W3107502112","https://openalex.org/W3107590933","https://openalex.org/W3107653507","https://openalex.org/W3108125093","https://openalex.org/W3108560336","https://openalex.org/W3109470472","https://openalex.org/W3110486195","https://openalex.org/W3120804725","https://openalex.org/W3150112631","https://openalex.org/W3154061064","https://openalex.org/W3159770254","https://openalex.org/W3163799992","https://openalex.org/W3165745140","https://openalex.org/W3170841864","https://openalex.org/W3175294391","https://openalex.org/W3176820334","https://openalex.org/W3202115483","https://openalex.org/W3205231674","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6637618735","https://openalex.org/W6639480849","https://openalex.org/W6681588610","https://openalex.org/W6683590716","https://openalex.org/W6685380521","https://openalex.org/W6695692224","https://openalex.org/W6730623217","https://openalex.org/W6739696289","https://openalex.org/W6746262046","https://openalex.org/W6746282794","https://openalex.org/W6766978945","https://openalex.org/W6767127972","https://openalex.org/W6767268582","https://openalex.org/W6795306211","https://openalex.org/W6797399245"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W3203792196","https://openalex.org/W2955455867","https://openalex.org/W4295929828","https://openalex.org/W3156096827"],"abstract_inverted_index":{"With":[0],"the":[1,18,56,60,65,73,93,106,109,119,158,167,171,177,183,187,191,198,213,222],"rapid":[2],"development":[3],"of":[4,38,215],"convolutional":[5],"neural":[6],"networks":[7],"(CNNs),":[8],"significant":[9],"progress":[10],"has":[11],"been":[12],"achieved":[13],"in":[14,98,166,186,228],"semantic":[15,81],"segmentation.":[16],"Despite":[17],"great":[19],"success,":[20],"such":[21],"deep":[22],"learning":[23,165],"approaches":[24],"require":[25],"large":[26],"scale":[27],"real-world":[28,74],"datasets":[29],"with":[30,50,64,118,221,226],"pixel-level":[31,36],"annotations.":[32,52],"However,":[33],"considering":[34],"that":[35],"labeling":[37],"semantics":[39],"is":[40,160,194],"extremely":[41],"laborious,":[42],"many":[43],"researchers":[44],"turn":[45],"to":[46,55,69,116,176,181,196],"utilize":[47],"synthetic":[48,66],"data":[49],"free":[51],"But":[53],"due":[54],"clear":[57],"domain":[58,77,94],"gap,":[59],"segmentation":[61,82,172],"model":[62,135,173,184],"trained":[63],"images":[67],"tends":[68],"perform":[70],"poorly":[71],"on":[72,204],"datasets.":[75],"Unsupervised":[76],"adaptation":[78,159],"(UDA)":[79],"for":[80],"recently":[83],"gains":[84],"an":[85],"increasing":[86],"research":[87],"attention,":[88],"which":[89,141],"aims":[90],"at":[91],"alleviating":[92],"discrepancy.":[95],"Existing":[96],"methods":[97],"this":[99,127],"scope":[100],"either":[101],"simply":[102],"align":[103],"features":[104],"or":[105,114],"outputs":[107],"across":[108,201],"source":[110],"and":[111,123,149,210,230],"target":[112],"domains":[113],"have":[115],"deal":[117],"complex":[120],"image":[121],"processing":[122],"post-processing":[124],"problems.":[125],"In":[126],"work,":[128],"we":[129],"propose":[130],"a":[131,143,150],"novel":[132],"multi-level":[133],"UDA":[134,207],"named":[136],"Confidence-and-Refinement":[137],"Adaptation":[138],"Model":[139],"(CRAM),":[140],"contains":[142],"confidence-aware":[144],"entropy":[145],"alignment":[146,153],"(CEA)":[147],"module":[148,193],"style":[151],"feature":[152,189],"(SFA)":[154],"module.":[155],"Through":[156],"CEA,":[157],"done":[161],"locally":[162],"via":[163],"adversarial":[164],"output":[168],"space,":[169,190],"making":[170],"pay":[174],"attention":[175],"high-confident":[178],"predictions.":[179],"Furthermore,":[180],"enhance":[182],"transfer":[185],"shallow":[188],"SFA":[192],"applied":[195],"minimize":[197],"appearance":[199],"gap":[200],"domains.":[202],"Experiments":[203],"two":[205],"challenging":[206],"benchmarks":[208],"\u201cGTA5-to-Cityscapes\u201d":[209],"\u201cSYNTHIA-to-Cityscapes\u201d":[211],"demonstrate":[212],"effectiveness":[214],"CRAM.":[216],"We":[217],"achieve":[218],"comparable":[219],"performance":[220],"existing":[223],"state-of-the-art":[224],"works":[225],"advantages":[227],"simplicity":[229],"convergence":[231],"speed.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}
