{"id":"https://openalex.org/W2968696051","doi":"https://doi.org/10.1109/tpami.2019.2960224","title":"Semi-Supervised Semantic Segmentation With High- and Low-Level Consistency","display_name":"Semi-Supervised Semantic Segmentation With High- and Low-Level Consistency","publication_year":2019,"publication_date":"2019-12-17","ids":{"openalex":"https://openalex.org/W2968696051","doi":"https://doi.org/10.1109/tpami.2019.2960224","mag":"2968696051","pmid":"https://pubmed.ncbi.nlm.nih.gov/31869780"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2019.2960224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2960224","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.05724","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102749577","display_name":"Sudhanshu Mittal","orcid":"https://orcid.org/0000-0002-7809-8058"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sudhanshu Mittal","raw_affiliation_strings":["Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany","[Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany]"],"raw_orcid":"https://orcid.org/0000-0002-7809-8058","affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany","institution_ids":["https://openalex.org/I161046081"]},{"raw_affiliation_string":"[Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany]","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024043201","display_name":"Maxim Tatarchenko","orcid":"https://orcid.org/0000-0003-1988-1488"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maxim Tatarchenko","raw_affiliation_strings":["Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany","[Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany]"],"raw_orcid":"https://orcid.org/0000-0003-1988-1488","affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany","institution_ids":["https://openalex.org/I161046081"]},{"raw_affiliation_string":"[Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany]","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070290355","display_name":"Thomas Brox","orcid":"https://orcid.org/0000-0002-6282-8861"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Brox","raw_affiliation_strings":["Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany","Albert-Ludwigs Univ. of Freiburg"],"raw_orcid":"https://orcid.org/0000-0002-6282-8861","affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Freiburg, Freiburg im Breisgau, Germany","institution_ids":["https://openalex.org/I161046081"]},{"raw_affiliation_string":"Albert-Ludwigs Univ. of Freiburg","institution_ids":["https://openalex.org/I161046081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161046081"],"apc_list":null,"apc_paid":null,"fwci":1.0158,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.80959879,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"43","issue":"4","first_page":"1369","last_page":"1379"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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":0.9993000030517578,"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/pascal","display_name":"Pascal (unit)","score":0.9100150465965271},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7603336572647095},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7487739324569702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7260996699333191},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5266326069831848},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5258287191390991},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4871537387371063},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4800478219985962},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.46211010217666626},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4279704988002777},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13404718041419983}],"concepts":[{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.9100150465965271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7603336572647095},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7487739324569702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7260996699333191},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5266326069831848},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5258287191390991},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4871537387371063},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4800478219985962},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.46211010217666626},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4279704988002777},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13404718041419983},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tpami.2019.2960224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2960224","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:31869780","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31869780","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:1908.05724","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.05724","pdf_url":"https://arxiv.org/pdf/1908.05724","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2968696051","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1908.05724","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1908.05724","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1908.05724","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.05724","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.05724","pdf_url":"https://arxiv.org/pdf/1908.05724","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2968696051.pdf","grobid_xml":"https://content.openalex.org/works/W2968696051.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W586034241","https://openalex.org/W1495267108","https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W1945608308","https://openalex.org/W2031489346","https://openalex.org/W2095705004","https://openalex.org/W2099471712","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2125215748","https://openalex.org/W2144794286","https://openalex.org/W2194775991","https://openalex.org/W2221898772","https://openalex.org/W2337429362","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2432004435","https://openalex.org/W2530816535","https://openalex.org/W2552414813","https://openalex.org/W2554423077","https://openalex.org/W2563705555","https://openalex.org/W2598666589","https://openalex.org/W2600144439","https://openalex.org/W2752782242","https://openalex.org/W2778764040","https://openalex.org/W2798376494","https://openalex.org/W2808223045","https://openalex.org/W2899771611","https://openalex.org/W2953070460","https://openalex.org/W2962758679","https://openalex.org/W2963420686","https://openalex.org/W2963483401","https://openalex.org/W2963687373","https://openalex.org/W2963727650","https://openalex.org/W2964121744","https://openalex.org/W2964159205","https://openalex.org/W2964288706","https://openalex.org/W2964309882","https://openalex.org/W3136198447","https://openalex.org/W6617210626","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6640295612","https://openalex.org/W6674330103","https://openalex.org/W6688657083","https://openalex.org/W6718379498","https://openalex.org/W6729856380","https://openalex.org/W6733814495","https://openalex.org/W6748481559","https://openalex.org/W6748692255","https://openalex.org/W6756040250","https://openalex.org/W6757712183","https://openalex.org/W6764051988","https://openalex.org/W6791883635"],"related_works":["https://openalex.org/W1983546589","https://openalex.org/W3203484389","https://openalex.org/W3130223701","https://openalex.org/W3090212082","https://openalex.org/W3091067756","https://openalex.org/W2124343550","https://openalex.org/W3102166635","https://openalex.org/W3204025806","https://openalex.org/W3110002552","https://openalex.org/W3153332184","https://openalex.org/W2911686375","https://openalex.org/W3047233942","https://openalex.org/W2910957910","https://openalex.org/W2968706510","https://openalex.org/W2766945538","https://openalex.org/W2215086518","https://openalex.org/W3180084241","https://openalex.org/W2783366437","https://openalex.org/W3094938797","https://openalex.org/W1983521647"],"abstract_inverted_index":{"The":[0,62,93,110],"ability":[1],"to":[2,74],"understand":[3],"visual":[4],"information":[5],"from":[6,52,76],"limited":[7,32,53],"labeled":[8,124],"data":[9,33],"is":[10],"an":[11,44],"important":[12],"aspect":[13],"of":[14],"machine":[15],"learning.":[16,141],"While":[17],"image-level":[18],"classification":[19,30,87],"has":[20,34],"been":[21],"extensively":[22],"studied":[23],"in":[24,139],"a":[25,70],"semi-supervised":[26,47,86,89,140],"setting,":[27],"dense":[28],"pixel-level":[29],"with":[31,69,88,107,121],"only":[35],"drawn":[36],"attention":[37],"recently.":[38],"In":[39],"this":[40],"work,":[41],"we":[42],"propose":[43],"approach":[45,64,95,111,135],"for":[46],"semantic":[48],"segmentation":[49,90],"that":[50,84],"learns":[51],"pixel-wise":[54],"annotated":[55],"samples":[56],"while":[57],"exploiting":[58],"additional":[59],"annotation-free":[60],"images.":[61,78],"proposed":[63],"relies":[65],"on":[66],"adversarial":[67],"training":[68,106],"feature":[71],"matching":[72],"loss":[73],"learn":[75],"unlabeled":[77],"It":[79],"uses":[80],"two":[81],"network":[82],"branches":[83],"link":[85],"including":[91],"self-training.":[92],"dual-branch":[94],"reduces":[96],"both":[97],"the":[98,101],"low-level":[99],"and":[100,133],"high-level":[102],"artifacts":[103],"typical":[104],"when":[105,119],"few":[108,123],"labels.":[109],"attains":[112],"significant":[113],"improvement":[114],"over":[115],"existing":[116],"methods,":[117],"especially":[118],"trained":[120],"very":[122],"samples.":[125],"On":[126],"several":[127],"standard":[128],"benchmarks-PASCAL":[129],"VOC":[130],"2012,":[131],"PASCAL-Context,":[132],"Cityscapes-the":[134],"achieves":[136],"new":[137],"state-of-the-art":[138]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
