{"id":"https://openalex.org/W3112561780","doi":"https://doi.org/10.1109/tnnls.2022.3155746","title":"Self-Training for Class-Incremental Semantic Segmentation","display_name":"Self-Training for Class-Incremental Semantic Segmentation","publication_year":2022,"publication_date":"2022-03-17","ids":{"openalex":"https://openalex.org/W3112561780","doi":"https://doi.org/10.1109/tnnls.2022.3155746","mag":"3112561780","pmid":"https://pubmed.ncbi.nlm.nih.gov/35298386"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3155746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3155746","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5102765121","display_name":"Lu Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lu Yu","raw_affiliation_strings":["School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026904363","display_name":"Xialei Liu","orcid":"https://orcid.org/0000-0001-8534-3026"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xialei Liu","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101958996","display_name":"Joost van de Weijer","orcid":"https://orcid.org/0000-0002-9656-9706"},"institutions":[{"id":"https://openalex.org/I123044942","display_name":"Universitat Aut\u00f2noma de Barcelona","ror":"https://ror.org/052g8jq94","country_code":"ES","type":"education","lineage":["https://openalex.org/I123044942"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Joost van de Weijer","raw_affiliation_strings":["Computer Vision Center, Autonomous University of Barcelona, Bellaterra, Spain"],"affiliations":[{"raw_affiliation_string":"Computer Vision Center, Autonomous University of Barcelona, Bellaterra, Spain","institution_ids":["https://openalex.org/I123044942"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102765121"],"corresponding_institution_ids":["https://openalex.org/I136765683"],"apc_list":null,"apc_paid":null,"fwci":6.8936,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.97337788,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"34","issue":"11","first_page":"9116","last_page":"9127"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.998199999332428,"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":0.9944000244140625,"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/forgetting","display_name":"Forgetting","score":0.8249901533126831},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7884666323661804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.636157751083374},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6250259876251221},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6187529563903809},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6184883713722229},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5591278076171875},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5279673337936401},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.48866918683052063},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.46376487612724304},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4633615016937256},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4127460718154907},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08703333139419556}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.8249901533126831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7884666323661804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.636157751083374},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6250259876251221},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6187529563903809},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6184883713722229},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5591278076171875},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5279673337936401},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48866918683052063},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.46376487612724304},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4633615016937256},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4127460718154907},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08703333139419556},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3155746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3155746","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35298386","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35298386","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W1682403713","https://openalex.org/W1745334888","https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W2037603696","https://openalex.org/W2106401878","https://openalex.org/W2118045473","https://openalex.org/W2145494108","https://openalex.org/W2186094539","https://openalex.org/W2194775991","https://openalex.org/W2293363371","https://openalex.org/W2412782625","https://openalex.org/W2473930607","https://openalex.org/W2559785631","https://openalex.org/W2560023338","https://openalex.org/W2560647685","https://openalex.org/W2587989515","https://openalex.org/W2630837129","https://openalex.org/W2732026016","https://openalex.org/W2737258237","https://openalex.org/W2737492962","https://openalex.org/W2743151379","https://openalex.org/W2786446225","https://openalex.org/W2788388592","https://openalex.org/W2791091755","https://openalex.org/W2802198257","https://openalex.org/W2807445254","https://openalex.org/W2884282566","https://openalex.org/W2895281799","https://openalex.org/W2921749009","https://openalex.org/W2948734064","https://openalex.org/W2955058313","https://openalex.org/W2962891704","https://openalex.org/W2962966271","https://openalex.org/W2963072899","https://openalex.org/W2963073398","https://openalex.org/W2963178577","https://openalex.org/W2963560049","https://openalex.org/W2963588172","https://openalex.org/W2963881378","https://openalex.org/W2963896186","https://openalex.org/W2964189064","https://openalex.org/W2964309882","https://openalex.org/W2965391153","https://openalex.org/W2966865642","https://openalex.org/W2974777596","https://openalex.org/W2982220706","https://openalex.org/W2985406498","https://openalex.org/W3005498204","https://openalex.org/W3011986058","https://openalex.org/W3013325675","https://openalex.org/W3030364939","https://openalex.org/W3034435444","https://openalex.org/W3035513921","https://openalex.org/W3080961686","https://openalex.org/W3098511564","https://openalex.org/W3101808799","https://openalex.org/W3105378872","https://openalex.org/W3108601100","https://openalex.org/W3132455321","https://openalex.org/W3134257222","https://openalex.org/W4297798436","https://openalex.org/W4301163820","https://openalex.org/W4301206121","https://openalex.org/W4319988532","https://openalex.org/W6639102338","https://openalex.org/W6677741084","https://openalex.org/W6681588610","https://openalex.org/W6732696085","https://openalex.org/W6733387591","https://openalex.org/W6739696289","https://openalex.org/W6741217325","https://openalex.org/W6748481559","https://openalex.org/W6751444130","https://openalex.org/W6765779288","https://openalex.org/W6772750526","https://openalex.org/W6791486786","https://openalex.org/W6849896277"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W2145559838","https://openalex.org/W3116498279","https://openalex.org/W4287549553","https://openalex.org/W3183027292","https://openalex.org/W4377086356","https://openalex.org/W1663079876","https://openalex.org/W3042343907","https://openalex.org/W4295335600"],"abstract_inverted_index":{"In":[0,92],"class-incremental":[1],"semantic":[2],"segmentation,":[3],"we":[4,36,56,131],"have":[5],"no":[6],"access":[7],"to":[8,38,98,154,170,183],"the":[9,63,71,80,84,88,100,108,124,129,134,141,161,178],"labeled":[10],"data":[11,73,136,143,151],"of":[12,28,52,83,102,168],"previous":[13,53,85,184],"tasks.":[14],"Therefore,":[15],"when":[16],"incrementally":[17],"learning":[18],"new":[19],"classes,":[20],"deep":[21],"neural":[22],"networks":[23],"suffer":[24],"from":[25,79,106,140],"catastrophic":[26],"forgetting":[27],"previously":[29],"learned":[30],"knowledge.":[31,54],"To":[32],"address":[33],"this":[34],"problem,":[35],"propose":[37],"apply":[39],"a":[40,59,165],"self-training":[41],"approach":[42],"that":[43,115,133,145],"leverages":[44],"unlabeled":[45,72],"data,":[46],"which":[47],"is":[48,96],"used":[49],"for":[50,62,70],"rehearsal":[51],"Specifically,":[55],"first":[57],"learn":[58],"temporary":[60,90,111],"model":[61,82],"current":[64,89],"task,":[65],"and":[66,87,110,144,175],"then,":[67],"pseudo":[68,103],"labels":[69,104],"are":[74],"computed":[75],"by":[76,122],"fusing":[77],"information":[78],"old":[81,109],"task":[86],"model.":[91],"addition,":[93],"conflict":[94],"reduction":[95],"proposed":[97],"resolve":[99],"conflicts":[101],"generated":[105],"both":[107],"models.":[112],"We":[113],"show":[114,132],"maximizing":[116],"self-entropy":[117],"can":[118,137,152],"further":[119],"improve":[120],"results":[121],"smoothing":[123],"overconfident":[125],"predictions.":[126],"Interestingly,":[127],"in":[128],"experiments,":[130],"auxiliary":[135,150],"be":[138],"different":[139],"training":[142],"even":[146],"general-purpose,":[147],"but":[148],"diverse":[149],"lead":[153],"large":[155],"performance":[156],"gains.":[157],"The":[158],"experiments":[159],"demonstrate":[160],"state-of-the-art":[162,185],"results:":[163],"obtaining":[164],"relative":[166],"gain":[167],"up":[169],"114%":[171],"on":[172,177],"Pascal-VOC":[173],"2012":[174],"8.5%":[176],"more":[179],"challenging":[180],"ADE20K":[181],"compared":[182],"methods.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}