{"id":"https://openalex.org/W4292973282","doi":"https://doi.org/10.1109/tpami.2022.3200865","title":"Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks","display_name":"Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks","publication_year":2022,"publication_date":"2022-08-22","ids":{"openalex":"https://openalex.org/W4292973282","doi":"https://doi.org/10.1109/tpami.2022.3200865","pmid":"https://pubmed.ncbi.nlm.nih.gov/37819811"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3200865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3200865","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":"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/A5100655948","display_name":"Da-Wei Zhou","orcid":"https://orcid.org/0000-0001-7226-7773"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Da-Wei Zhou","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065180062","display_name":"Han-Jia Ye","orcid":"https://orcid.org/0000-0003-1173-1880"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han-Jia Ye","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035843722","display_name":"Liang Ma","orcid":"https://orcid.org/0000-0003-4228-258X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Ma","raw_affiliation_strings":["Hikvision Research Institute, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hikvision Research Institute, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636142","display_name":"Di Xie","orcid":"https://orcid.org/0000-0001-8065-5901"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di Xie","raw_affiliation_strings":["Hikvision Research Institute, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hikvision Research Institute, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085955762","display_name":"Shiliang Pu","orcid":"https://orcid.org/0000-0001-5269-7821"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shiliang Pu","raw_affiliation_strings":["Hikvision Research Institute, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hikvision Research Institute, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"De-Chuan Zhan","orcid":"https://orcid.org/0000-0001-9303-2519"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"De-Chuan Zhan","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100655948"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":17.4886,"has_fulltext":false,"cited_by_count":136,"citation_normalized_percentile":{"value":0.99400188,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"45","issue":"11","first_page":"12816","last_page":"12831"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9754999876022339,"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/T11243","display_name":"Respiratory viral infections research","score":0.9675999879837036,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7689284086227417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6407662630081177},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.6336327791213989},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5971612930297852},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5790619850158691},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5182650089263916},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4640715718269348},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4272170066833496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7689284086227417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6407662630081177},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.6336327791213989},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5971612930297852},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5790619850158691},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5182650089263916},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4640715718269348},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4272170066833496},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3200865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3200865","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:37819811","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37819811","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}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G2953444090","display_name":null,"funder_award_id":"62006112","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5072222428","display_name":null,"funder_award_id":"61773198","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G528746023","display_name":null,"funder_award_id":"61921006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":139,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1997121481","https://openalex.org/W2037979274","https://openalex.org/W2064675550","https://openalex.org/W2108598243","https://openalex.org/W2108767394","https://openalex.org/W2109579504","https://openalex.org/W2117539524","https://openalex.org/W2170296202","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2412094331","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2561272927","https://openalex.org/W2597655663","https://openalex.org/W2601450892","https://openalex.org/W2602516395","https://openalex.org/W2604763608","https://openalex.org/W2734314755","https://openalex.org/W2753160622","https://openalex.org/W2794757725","https://openalex.org/W2796346823","https://openalex.org/W2798836702","https://openalex.org/W2806984819","https://openalex.org/W2884282566","https://openalex.org/W2888541716","https://openalex.org/W2896457183","https://openalex.org/W2902625698","https://openalex.org/W2902723124","https://openalex.org/W2948734064","https://openalex.org/W2949736877","https://openalex.org/W2954929116","https://openalex.org/W2963341924","https://openalex.org/W2963540014","https://openalex.org/W2963542740","https://openalex.org/W2963563276","https://openalex.org/W2963580001","https://openalex.org/W2963588172","https://openalex.org/W2963741406","https://openalex.org/W2964105864","https://openalex.org/W2964189064","https://openalex.org/W2979324907","https://openalex.org/W2981864462","https://openalex.org/W2986604550","https://openalex.org/W2995139074","https://openalex.org/W3012255272","https://openalex.org/W3012942774","https://openalex.org/W3030364939","https://openalex.org/W3034445277","https://openalex.org/W3034503642","https://openalex.org/W3034512672","https://openalex.org/W3034856281","https://openalex.org/W3034911677","https://openalex.org/W3034942609","https://openalex.org/W3035342403","https://openalex.org/W3035374961","https://openalex.org/W3035418072","https://openalex.org/W3035501943","https://openalex.org/W3091905774","https://openalex.org/W3094502228","https://openalex.org/W3094953068","https://openalex.org/W3096609285","https://openalex.org/W3105913416","https://openalex.org/W3113584014","https://openalex.org/W3117450517","https://openalex.org/W3118608800","https://openalex.org/W3131500599","https://openalex.org/W3155876088","https://openalex.org/W3157559713","https://openalex.org/W3174027668","https://openalex.org/W3174868646","https://openalex.org/W3175270254","https://openalex.org/W3175337163","https://openalex.org/W3175771944","https://openalex.org/W3176779063","https://openalex.org/W3177034761","https://openalex.org/W3177494822","https://openalex.org/W3180392831","https://openalex.org/W3202469562","https://openalex.org/W3203354307","https://openalex.org/W3205597769","https://openalex.org/W3207580420","https://openalex.org/W3208853938","https://openalex.org/W4205702529","https://openalex.org/W4206706211","https://openalex.org/W4214769349","https://openalex.org/W4226134030","https://openalex.org/W4226137555","https://openalex.org/W4281773771","https://openalex.org/W4289382675","https://openalex.org/W4292779060","https://openalex.org/W4294646197","https://openalex.org/W4295312788","https://openalex.org/W4295883599","https://openalex.org/W4300514939","https://openalex.org/W4301163820","https://openalex.org/W4304149893","https://openalex.org/W4313028293","https://openalex.org/W4385245566","https://openalex.org/W6638523607","https://openalex.org/W6687483927","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6735377749","https://openalex.org/W6736057607","https://openalex.org/W6739901393","https://openalex.org/W6741217325","https://openalex.org/W6742852309","https://openalex.org/W6743661861","https://openalex.org/W6744580074","https://openalex.org/W6748136086","https://openalex.org/W6749745641","https://openalex.org/W6750254146","https://openalex.org/W6751907932","https://openalex.org/W6751959828","https://openalex.org/W6755207826","https://openalex.org/W6755318597","https://openalex.org/W6755365793","https://openalex.org/W6756764172","https://openalex.org/W6757384668","https://openalex.org/W6758126075","https://openalex.org/W6766978945","https://openalex.org/W6770404601","https://openalex.org/W6774715050","https://openalex.org/W6778485988","https://openalex.org/W6778883912","https://openalex.org/W6779874285","https://openalex.org/W6779879114","https://openalex.org/W6783596713","https://openalex.org/W6784333009","https://openalex.org/W6787972765","https://openalex.org/W6788071488","https://openalex.org/W6788556936","https://openalex.org/W6795846790","https://openalex.org/W6797636097","https://openalex.org/W6802647179","https://openalex.org/W6810907504","https://openalex.org/W6838571599"],"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/W4310285384","https://openalex.org/W2794885965","https://openalex.org/W2104218666","https://openalex.org/W2959635497"],"abstract_inverted_index":{"New":[0],"classes":[1,26,54,58,168],"arise":[2],"frequently":[3],"in":[4,11,19,146],"our":[5],"ever-changing":[6],"world,":[7],"e.g.,":[8],"emerging":[9],"topics":[10],"social":[12],"media":[13],"and":[14,27,106,136,144,169,183,185],"new":[15,25,53,71,137,167],"types":[16],"of":[17,50,96],"products":[18],"e-commerce.":[20],"A":[21],"model":[22],"should":[23],"recognize":[24],"meanwhile":[28,170],"maintain":[29],"discriminability":[30],"over":[31,173],"old":[32,57,133,174],"classes.":[33,175],"Under":[34],"severe":[35],"circumstances,":[36],"only":[37],"limited":[38],"novel":[39],"instances":[40],"are":[41],"available":[42],"to":[43,166],"incrementally":[44],"update":[45],"the":[46,90,102,115,132,141,147,156],"model.":[47],"The":[48,93,150],"task":[49],"recognizing":[51],"few-shot":[52,61],"without":[55],"forgetting":[56,172],"is":[59,99],"called":[60],"class-incremental":[62],"learning":[63],"(FSCIL).":[64],"In":[65],"this":[66],"work,":[67],"we":[68,107],"propose":[69],"a":[70,110,124,160],"paradigm":[72],"for":[73,114],"FSCIL":[74,87],"based":[75,127],"on":[76,128,177],"meta-learning":[77],"by":[78],"LearnIng":[79],"Multi-phase":[80],"Incremental":[81],"Tasks":[82],"(Limit),":[83],"which":[84,130],"synthesizes":[85],"fake":[86,97],"tasks":[88,98,117],"from":[89],"base":[91],"dataset.":[92],"data":[94],"format":[95],"consistent":[100],"with":[101,159],"'real'":[103],"incremental":[104],"tasks,":[105],"can":[108],"build":[109],"generalizable":[111],"feature":[112],"space":[113],"unseen":[116],"through":[118],"meta-learning.":[119],"Besides,":[120],"Limit":[121,163,193],"also":[122,153],"constructs":[123],"calibration":[125,151],"module":[126,152],"transformer,":[129],"calibrates":[131],"class":[134,138],"classifiers":[135],"prototypes":[139],"into":[140],"same":[142],"scale":[143],"fills":[145],"semantic":[148],"gap.":[149],"adaptively":[154],"contextualizes":[155],"instance-specific":[157],"embedding":[158],"set-to-set":[161],"function.":[162],"efficiently":[164],"adapts":[165],"resists":[171],"Experiments":[176],"three":[178],"benchmark":[179],"datasets":[180],"(CIFAR100,":[181],"miniImageNet,":[182],"CUB200)":[184],"large-scale":[186],"dataset,":[187],"i.e.,":[188],"ImageNet":[189],"ILSVRC2012":[190],"validate":[191],"that":[192],"achieves":[194],"state-of-the-art":[195],"performance.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":64},{"year":2024,"cited_by_count":41},{"year":2023,"cited_by_count":21}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}