{"id":"https://openalex.org/W2963343500","doi":"https://doi.org/10.1109/icassp.2018.8462111","title":"A Fully Convolutional Tri-Branch Network (FCTN) for Domain Adaptation","display_name":"A Fully Convolutional Tri-Branch Network (FCTN) for Domain Adaptation","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2963343500","doi":"https://doi.org/10.1109/icassp.2018.8462111","mag":"2963343500"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8462111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100723093","display_name":"Junting Zhang","orcid":"https://orcid.org/0000-0002-0019-6803"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Junting Zhang","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012788560","display_name":"Liang Chen","orcid":"https://orcid.org/0000-0001-5591-5951"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Liang","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001082656","display_name":"C.\u2010C. Jay Kuo","orcid":"https://orcid.org/0000-0001-9474-5035"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C.-C. Jay Kuo","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100723093"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":3.2375,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93767732,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3001","last_page":"3005"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9962999820709229,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9954000115394592,"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":0.822669506072998},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8052898049354553},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7369568943977356},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.704537034034729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6971991062164307},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.692936897277832},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6884211301803589},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5203465819358826},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5165128111839294},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5046473741531372},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.474710613489151},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.332328200340271},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2393774688243866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10635867714881897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.822669506072998},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8052898049354553},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7369568943977356},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.704537034034729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6971991062164307},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.692936897277832},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6884211301803589},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5203465819358826},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5165128111839294},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5046473741531372},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.474710613489151},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.332328200340271},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2393774688243866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10635867714881897},{"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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8462111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1923697677","https://openalex.org/W2048679005","https://openalex.org/W2133556223","https://openalex.org/W2159291411","https://openalex.org/W2214409633","https://openalex.org/W2223259665","https://openalex.org/W2271840356","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2562192638","https://openalex.org/W2593768305","https://openalex.org/W2594718649","https://openalex.org/W2739759330","https://openalex.org/W2756073160","https://openalex.org/W2964288524","https://openalex.org/W2964344719","https://openalex.org/W3101281919","https://openalex.org/W6637373629","https://openalex.org/W6640295612","https://openalex.org/W6683633756","https://openalex.org/W6722836162","https://openalex.org/W6734871034","https://openalex.org/W6735050833","https://openalex.org/W6746022572"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W4312246223","https://openalex.org/W3105973526"],"abstract_inverted_index":{"A":[0],"domain":[1,32,84],"adaptation":[2,85],"method":[3],"for":[4],"urban":[5],"scene":[6],"segmentation":[7],"is":[8,37,96],"proposed":[9,80],"in":[10,28,44],"this":[11,56],"work.":[12],"We":[13,77],"develop":[14],"a":[15,68,111],"fully":[16],"convolutional":[17],"tri-branch":[18,59],"network,":[19],"where":[20],"two":[21],"branches":[22],"assign":[23],"pseudo":[24],"labels":[25],"to":[26],"images":[27,43],"the":[29,34,45,58,70,74,79,102],"unlabeled":[30],"target":[31,47],"while":[33],"third":[35],"branch":[36],"trained":[38],"with":[39],"supervision":[40],"based":[41],"on":[42,82],"pseudo-labeled":[46],"domain.":[48],"The":[49],"re-labeling":[50],"and":[51,91,105],"re-training":[52],"processes":[53],"alternate.":[54],"With":[55],"design,":[57],"network":[60,81],"learns":[61],"target-specific":[62],"discriminative":[63],"representations":[64],"progressively":[65],"and,":[66],"as":[67],"result,":[69],"cross-domain":[71],"capability":[72],"of":[73],"segmenter":[75],"improves.":[76],"evaluate":[78],"large-scale":[83],"experiments":[86],"using":[87],"both":[88],"synthetic":[89],"(GTA)":[90],"real":[92],"(Cityscapes)":[93],"images.":[94],"It":[95],"shown":[97],"that":[98],"our":[99],"solution":[100],"achieves":[101],"state-of-the-art":[103],"performance":[104],"it":[106],"outperforms":[107],"previous":[108],"methods":[109],"by":[110],"significant":[112],"margin.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":5}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}
