{"id":"https://openalex.org/W4402980321","doi":"https://doi.org/10.1109/icme57554.2024.10687420","title":"Delve into Source and Target Collaboration in Semi-supervised Domain Adaptation for Semantic Segmentation","display_name":"Delve into Source and Target Collaboration in Semi-supervised Domain Adaptation for Semantic Segmentation","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402980321","doi":"https://doi.org/10.1109/icme57554.2024.10687420"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10687420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10687420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5101437985","display_name":"Yuan Gao","orcid":"https://orcid.org/0000-0002-8428-034X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Gao","raw_affiliation_strings":["University of Science and Technology of China,MoE Key Laboratory of Brain-Inspired, Intelligent Perception and Cognition,Hefei,China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,MoE Key Laboratory of Brain-Inspired, Intelligent Perception and Cognition,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376572","display_name":"Zilei Wang","orcid":"https://orcid.org/0000-0003-1822-3731"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilei Wang","raw_affiliation_strings":["University of Science and Technology of China,MoE Key Laboratory of Brain-Inspired, Intelligent Perception and Cognition,Hefei,China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,MoE Key Laboratory of Brain-Inspired, Intelligent Perception and Cognition,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351200","display_name":"Yixin Zhang","orcid":"https://orcid.org/0000-0002-0476-9066"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixin Zhang","raw_affiliation_strings":["University of Science and Technology of China,Institute of Artificial Intelligence,Hefei Comprehensive National Science Center,Hefei,China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,Institute of Artificial Intelligence,Hefei Comprehensive National Science Center,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101437985"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.6982,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76062429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9869999885559082,"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":0.9869999885559082,"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":0.7658562660217285},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6727780103683472},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6168211102485657},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6057111024856567},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5773664712905884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41269010305404663},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3748684823513031},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07014742493629456},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.0598946213722229}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7658562660217285},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6727780103683472},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6168211102485657},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6057111024856567},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5773664712905884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41269010305404663},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3748684823513031},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07014742493629456},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0598946213722229},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"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":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10687420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10687420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2031489346","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2997910357","https://openalex.org/W3034590424","https://openalex.org/W3106895564","https://openalex.org/W3120562181","https://openalex.org/W3120804725","https://openalex.org/W3171581326","https://openalex.org/W3175294391","https://openalex.org/W3176969075","https://openalex.org/W3217147624","https://openalex.org/W4291961281","https://openalex.org/W4312310512","https://openalex.org/W4313184106","https://openalex.org/W4382468766","https://openalex.org/W6754892417","https://openalex.org/W6797399245","https://openalex.org/W6802946413"],"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":{"Semi-supervised":[0],"domain":[1,17,24,28,120],"adaptation":[2],"(SSDA)":[3],"for":[4,104],"semantic":[5],"segmentation":[6],"aims":[7],"to":[8,32,37,51,90,112,143,148],"train":[9],"a":[10,78,139],"model":[11,54,70],"that":[12],"performs":[13],"well":[14,46],"on":[15,82,172],"target":[16,27,122,151],"by":[18,95,118],"learning":[19],"from":[20,42,65,92],"both":[21,43,66],"fully-labeled":[22],"source":[23,119],"and":[25,69,121,129,176],"partially-labeled":[26],"data.":[29,102,135],"The":[30],"key":[31],"this":[33,58,63,74],"task":[34,163],"is":[35,157,196],"how":[36],"collaborate":[38],"the":[39,48,53,105,115,145,154,162,165,177,180],"labeled":[40,106,134],"data":[41,67],"domains,":[44],"as":[45,47,153],"unlabeled":[49,101],"data,":[50,107],"benefit":[52],"training":[55],"complementarily.":[56],"In":[57],"paper,":[59],"we":[60,76,108,125,137],"innovatively":[61],"achieve":[62],"goal":[64],"combination":[68,132],"mergence":[71],"perspectives.":[72],"To":[73],"end,":[75],"propose":[77,126,138],"co-training":[79],"framework":[80],"based":[81],"siamese":[83],"networks,":[84],"where":[85],"two":[86,110,173],"networks":[87,111],"are":[88],"encouraged":[89],"learn":[91,114],"each":[93],"other":[94],"cross-supervision":[96],"with":[97,161,190],"pseudo":[98],"labels":[99],"of":[100,133,182],"Meanwhile,":[103],"enforce":[109],"separately":[113],"knowledge":[116],"dominated":[117],"domain.":[123],"Specifically,":[124],"domain-specific":[127],"initialization":[128],"differentiated":[130],"cross-domain":[131],"Moreover,":[136],"target-preferred":[140],"alignment":[141],"method":[142],"encourage":[144],"source-biased":[146,166],"network":[147,156],"optimize":[149],"towards":[150],"domain,":[152],"target-biased":[155],"more":[158],"in":[159],"line":[160],"than":[164],"network.":[167],"We":[168],"conduct":[169],"extensive":[170],"experiments":[171],"challenging":[174],"benchmarks,":[175],"results":[178],"demonstrate":[179],"effectiveness":[181],"our":[183],"method,":[184],"which":[185],"outperforms":[186],"previous":[187],"state-of-the-art":[188],"methods":[189],"considerable":[191],"performance":[192],"improvement.":[193],"Our":[194],"code":[195],"available":[197],"at":[198],"https://github.com/EdenHazardan/DSTC-SSDA.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
