{"id":"https://openalex.org/W4313178131","doi":"https://doi.org/10.1109/icarm54641.2022.9959401","title":"A Two-Stage Domain Adaptation Approach Based on Contrastive Learning and Unsupervised Semantic Segmentation","display_name":"A Two-Stage Domain Adaptation Approach Based on Contrastive Learning and Unsupervised Semantic Segmentation","publication_year":2022,"publication_date":"2022-07-09","ids":{"openalex":"https://openalex.org/W4313178131","doi":"https://doi.org/10.1109/icarm54641.2022.9959401"},"language":"en","primary_location":{"id":"doi:10.1109/icarm54641.2022.9959401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm54641.2022.9959401","pdf_url":null,"source":{"id":"https://openalex.org/S4363608069","display_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061919044","display_name":"Lei Wu","orcid":"https://orcid.org/0000-0002-9040-2702"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wu","raw_affiliation_strings":["National University of Defense Technology,College of Intelligence Science and Technology,Changsha,China,40073"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Intelligence Science and Technology,Changsha,China,40073","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011438608","display_name":"Tao Wu","orcid":"https://orcid.org/0000-0003-1344-835X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wu","raw_affiliation_strings":["National University of Defense Technology,College of Intelligence Science and Technology,Changsha,China,40073"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Intelligence Science and Technology,Changsha,China,40073","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102211751","display_name":"Meiping Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiping Shi","raw_affiliation_strings":["National University of Defense Technology,College of Intelligence Science and Technology,Changsha,China,40073"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology,College of Intelligence Science and Technology,Changsha,China,40073","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091784428","display_name":"Kai Cao","orcid":"https://orcid.org/0000-0002-9524-4942"},"institutions":[{"id":"https://openalex.org/I4210153068","display_name":"Dongfeng Motor Group (China)","ror":"https://ror.org/055ar4y96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210153068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Cao","raw_affiliation_strings":["Dongfeng USharing Technology Co.,Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongfeng USharing Technology Co.,Ltd","institution_ids":["https://openalex.org/I4210153068"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"2","issue":null,"first_page":"219","last_page":"225"},"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":1.0,"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":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9948999881744385,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9925000071525574,"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/computer-science","display_name":"Computer science","score":0.8485934734344482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7538671493530273},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7080509066581726},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5342473387718201},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5240521430969238},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5095524787902832},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47118616104125977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46758174896240234},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44683483242988586}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8485934734344482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7538671493530273},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7080509066581726},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5342473387718201},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5240521430969238},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5095524787902832},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47118616104125977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46758174896240234},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44683483242988586},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm54641.2022.9959401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm54641.2022.9959401","pdf_url":null,"source":{"id":"https://openalex.org/S4363608069","display_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1882958252","https://openalex.org/W2009172320","https://openalex.org/W2048074730","https://openalex.org/W2340897893","https://openalex.org/W2487365028","https://openalex.org/W2562192638","https://openalex.org/W2584009249","https://openalex.org/W2593768305","https://openalex.org/W2769672616","https://openalex.org/W2770180314","https://openalex.org/W2781604162","https://openalex.org/W2801780873","https://openalex.org/W2892614179","https://openalex.org/W2895281799","https://openalex.org/W2951939904","https://openalex.org/W2962808524","https://openalex.org/W2963107255","https://openalex.org/W2963784072","https://openalex.org/W2963865469","https://openalex.org/W2963983207","https://openalex.org/W2981540341","https://openalex.org/W2981925632","https://openalex.org/W2985406498","https://openalex.org/W3042615550","https://openalex.org/W3099193570","https://openalex.org/W3122412340","https://openalex.org/W3172288085","https://openalex.org/W6639480849","https://openalex.org/W6720691552","https://openalex.org/W6730623217","https://openalex.org/W6734871034","https://openalex.org/W6735204497","https://openalex.org/W6745842894","https://openalex.org/W6746148458","https://openalex.org/W6746282794","https://openalex.org/W6747654920","https://openalex.org/W6793555798"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2997567050","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008","https://openalex.org/W2053596378","https://openalex.org/W2168523118"],"abstract_inverted_index":{"As":[0],"a":[1,25,64],"pixel-level":[2,47,67],"prediction":[3,87,104,212],"task":[4],"in":[5,79,121,171,183,189,233],"computer":[6],"vision,":[7],"semantic":[8,29,57,86,166],"segmentation":[9,30,117,167],"relies":[10],"on":[11,215],"sufficient":[12],"and":[13,55,141,153,186,240],"relatively":[14],"fine":[15],"image":[16],"annotation":[17],"for":[18,32,85,203],"its":[19],"excellent":[20],"performance.":[21],"This":[22,218],"paper":[23],"proposes":[24],"more":[26,230],"flexible":[27],"two-stage":[28],"framework":[31],"domain":[33,185,191,235],"adaptation":[34,95,236],"from":[35],"virtual":[36,53,172],"scenes":[37,54,173],"to":[38,62,92,114,129,150,174,200,223],"real":[39,90,108],"street":[40,134,208],"scenes.":[41],"In":[42,70,100,126,206],"the":[43,60,71,74,80,89,94,97,103,107,130,148,156,161,221,234],"first":[44,81],"stage,":[45,73,102],"supervised":[46],"contrastive":[48],"learning":[49],"is":[50,83,213],"performed":[51,214],"using":[52],"their":[56],"labels,":[58],"enabling":[59,147],"model":[61,77,149],"learn":[63],"highly":[65],"structured":[66],"feature":[68],"space.":[69],"second":[72],"pixel":[75],"discriminant":[76],"obtained":[78,170],"stage":[82],"used":[84,111],"of":[88,96,106,118,133,145,238],"scene":[91,109,177],"achieve":[93,229],"target":[98,190,225],"domain.":[99],"this":[101,137,198],"results":[105,232],"are":[110],"as":[112,155],"pseudo-labels":[113],"perform":[115],"unsupervised":[116],"single-frame":[119],"images":[120],"an":[122],"iterative":[123,211],"training":[124],"manner.":[125],"particular,":[127],"according":[128],"sequence":[131],"characteristics":[132],"view":[135],"images,":[136,146],"method":[138,199],"iteratively":[139],"trains":[140],"predicts":[142],"consecutive":[143,216],"frames":[144],"be":[151,193],"fine-tuned":[152],"iterated":[154],"environment":[157,201],"changes.":[158],"By":[159],"exploring":[160],"above":[162],"framework,":[163],"we":[164,228],"use":[165],"labels":[168],"easily":[169],"carry":[175],"out":[176],"adaption.":[178],"More":[179],"importantly,":[180],"knowledge":[181],"mining":[182],"source":[184],"adaptive":[187],"adjustment":[188],"can":[192],"flexibly":[194],"independent.":[195],"We":[196],"apply":[197],"perception":[202],"autonomous":[204],"driving.":[205],"sequential":[207],"scenes,":[209],"dynamic":[210],"frames.":[217],"approach":[219],"enhances":[220],"adaptability":[222],"various":[224],"domains.":[226],"Finally":[227],"competitive":[231],"experiments":[237],"GTA->Cityscapes":[239],"GTA->ApolloScape.":[241]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}