{"id":"https://openalex.org/W4414856453","doi":"https://doi.org/10.1109/tmm.2025.3618570","title":"Multi-View Knowledge Guided Semantic Prototype Learning for Generalized Zero-Shot Action Recognition","display_name":"Multi-View Knowledge Guided Semantic Prototype Learning for Generalized Zero-Shot Action Recognition","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414856453","doi":"https://doi.org/10.1109/tmm.2025.3618570"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3618570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618570","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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":null,"display_name":"Ming-Zhe Li","orcid":"https://orcid.org/0009-0002-5391-5602"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Zhe Li","raw_affiliation_strings":["Pattern Recognition and Intelligent Systems Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","Pattern Recognition and Intelligent Systems Lab., School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-5391-5602","affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent Systems Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition and Intelligent Systems Lab., School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhen Jia","orcid":"https://orcid.org/0000-0002-6810-2279"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Jia","raw_affiliation_strings":["New Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6810-2279","affiliations":[{"raw_affiliation_string":"New Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang Zhang","orcid":"https://orcid.org/0000-0001-9425-3065"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Zhang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9425-3065","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084683676","display_name":"Yaoning Li","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaoning Li","raw_affiliation_strings":["New Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039812471","display_name":"Zhanyu Ma","orcid":"https://orcid.org/0000-0003-2950-2488"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanyu Ma","raw_affiliation_strings":["Pattern Recognition and Intelligent Systems Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","Pattern Recognition and Intelligent Systems Lab., School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2950-2488","affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent Systems Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition and Intelligent Systems Lab., School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":null,"display_name":"Liang Wang","orcid":"https://orcid.org/0000-0001-5224-8647"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Wang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5224-8647","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13759791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"9735","last_page":"9748"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9883000254631042,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9883000254631042,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.963100016117096,"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/action","display_name":"Action (physics)","score":0.6114000082015991},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42320001125335693},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.3978999853134155},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.38339999318122864},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.3790000081062317},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.3596000075340271},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.3513999879360199},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3422999978065491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8730000257492065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.679099977016449},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6114000082015991},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5734999775886536},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42320001125335693},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.3978999853134155},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.38339999318122864},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.3596000075340271},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.3296999931335449},{"id":"https://openalex.org/C201717286","wikidata":"https://www.wikidata.org/wiki/Q938185","display_name":"Rationality","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.2766999900341034},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3618570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3618570","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1627056226","display_name":null,"funder_award_id":"62373355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G172479822","display_name":null,"funder_award_id":"62225601","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4664901819","display_name":null,"funder_award_id":"62106260","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5156147101","display_name":null,"funder_award_id":"62236010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5180847182","display_name":null,"funder_award_id":"62306311","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7101706402","display_name":null,"funder_award_id":"L242025","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G8677236040","display_name":null,"funder_award_id":"U23B2052","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"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1983705368","https://openalex.org/W2056898157","https://openalex.org/W2098339052","https://openalex.org/W2106996050","https://openalex.org/W2603705233","https://openalex.org/W2751841288","https://openalex.org/W2802979841","https://openalex.org/W2897510511","https://openalex.org/W2900819232","https://openalex.org/W2944006115","https://openalex.org/W2947758001","https://openalex.org/W2962689421","https://openalex.org/W2963283377","https://openalex.org/W2963369114","https://openalex.org/W2964105864","https://openalex.org/W2964134613","https://openalex.org/W2969221728","https://openalex.org/W2972073579","https://openalex.org/W2985891137","https://openalex.org/W3002706955","https://openalex.org/W3014645216","https://openalex.org/W3035050855","https://openalex.org/W3101226978","https://openalex.org/W3109763349","https://openalex.org/W3118716190","https://openalex.org/W3185273257","https://openalex.org/W3195429019","https://openalex.org/W3209114016","https://openalex.org/W4285787895","https://openalex.org/W4312799843","https://openalex.org/W4313123992","https://openalex.org/W4367043742","https://openalex.org/W4387969459","https://openalex.org/W4388004144","https://openalex.org/W4388543864","https://openalex.org/W4390241289","https://openalex.org/W4390871852","https://openalex.org/W4393156340","https://openalex.org/W4394773602","https://openalex.org/W4399039553","https://openalex.org/W4399206512","https://openalex.org/W4400647163","https://openalex.org/W4402727545","https://openalex.org/W4403791161","https://openalex.org/W4403841197","https://openalex.org/W4405890988"],"related_works":[],"abstract_inverted_index":{"Generalized":[0],"zero-shot":[1],"skeleton-based":[2,208],"action":[3,38,48,53,82,90,108,153,200,209,225],"recognition":[4,150,210],"(GZSSAR)":[5],"is":[6,128,169],"an":[7,121],"emerging":[8],"and":[9,46,94,102,137,140,190,214,227,244],"challenging":[10],"problem":[11],"in":[12,77,143,161],"the":[13,42,51,57,65,80,133,149,187,191,196,219,222,228,234,237,242],"computer":[14],"vision":[15],"community.":[16],"It":[17,130],"requires":[18],"models":[19,160],"to":[20,40,68,70,79,112],"recognize":[21],"human":[22],"actions,":[23],"including":[24],"some":[25],"classes":[26],"that":[27,163],"are":[28,249],"unseen":[29,47,71,152,166],"during":[30],"training.":[31],"Previous":[32],"studies":[33],"typically":[34,158],"rely":[35],"solely":[36],"on":[37,195,205,252],"labels":[39],"bridge":[41],"gap":[43],"between":[44,199],"seen":[45],"classes.":[49,72,154,201],"However,":[50],"limited":[52],"semantic":[54,61,116,135,141,197],"information":[55,117],"hinders":[56],"learning":[58],"of":[59,88,151,221,236,246],"comprehensive":[60],"prototypes,":[62],"thereby":[63],"restricting":[64],"model's":[66],"ability":[67],"generalize":[69],"To":[73,174],"address":[74],"this":[75,247],"issue,":[76],"addition":[78],"original":[81],"labels,":[83],"we":[84,179],"explore":[85],"four":[86],"types":[87],"textual":[89],"descriptions":[91,96,226],"(i.e.,":[92],"interpretive":[93],"motional":[95],"derived":[97],"from":[98],"manual":[99],"expert":[100],"annotation":[101],"large":[103],"language":[104],"model)":[105],"for":[106,118,171],"each":[107],"class.":[109],"In":[110],"order":[111],"comprehensively":[113],"utilize":[114],"multi-view":[115,134,224],"zeroshot":[119],"classification,":[120],"Attentional":[122],"Multi-view":[123],"Semantic":[124],"Fusion":[125],"(AMSF)":[126],"model":[127,230],"proposed.":[129],"effectively":[131],"integrates":[132],"features":[136,142],"aligns":[138],"visual":[139],"a":[144],"common":[145],"space,":[146],"subsequently":[147],"realizing":[148],"Furthermore,":[155],"previous":[156],"works":[157],"evaluate":[159,176],"settings":[162],"include":[164],"specific":[165],"classes,":[167],"which":[168],"insufficient":[170],"GZSSAR":[172],"research.":[173],"thoroughly":[175],"different":[177],"models,":[178],"introduce":[180],"two":[181],"novel":[182,238],"distinct":[183],"experimental":[184,203,239],"settings,":[185],"termed":[186],"\u201ceasy":[188],"setting\u201d":[189],"\u201chard":[192],"setting\u201d,":[193],"based":[194],"similarities":[198],"Extensive":[202],"results":[204],"three":[206],"large-scale":[207],"benchmarks":[211],"(PKU-MMD,":[212],"NTU-60,":[213],"NTU-120)":[215],"not":[216],"only":[217],"validate":[218],"advantages":[220],"proposed":[223],"AMSF":[229],"but":[231],"also":[232],"demonstrate":[233],"rationality":[235],"settings.":[240],"All":[241],"data":[243],"code":[245],"paper":[248],"publicly":[250],"available":[251],"GitHub.":[253]},"counts_by_year":[],"updated_date":"2025-12-19T00:32:22.182498","created_date":"2025-10-10T00:00:00"}
