{"id":"https://openalex.org/W4381198912","doi":"https://doi.org/10.1109/tpami.2023.3287208","title":"Semantic and Temporal Contextual Correlation Learning for Weakly-Supervised Temporal Action Localization","display_name":"Semantic and Temporal Contextual Correlation Learning for Weakly-Supervised Temporal Action Localization","publication_year":2023,"publication_date":"2023-06-19","ids":{"openalex":"https://openalex.org/W4381198912","doi":"https://doi.org/10.1109/tpami.2023.3287208","pmid":"https://pubmed.ncbi.nlm.nih.gov/37335790"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3287208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3287208","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/A5114514396","display_name":"Jie Fu","orcid":"https://orcid.org/0000-0003-1496-3919"},"institutions":[{"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"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Fu","raw_affiliation_strings":["Zhengzhou University, ZhengZhou, Henan, China","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, ZhengZhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014526931","display_name":"Junyu Gao","orcid":"https://orcid.org/0000-0002-8105-5497"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":"Junyu Gao","raw_affiliation_strings":["State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"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":"Changsheng Xu","raw_affiliation_strings":["State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114514396"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I38877650","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":1.1054,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79502167,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"45","issue":"10","first_page":"12427","last_page":"12443"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":0.9932000041007996,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9921000003814697,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6582446098327637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6282477378845215},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.557838499546051},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5223230719566345},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.51199871301651},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3450419306755066}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6582446098327637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6282477378845215},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.557838499546051},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5223230719566345},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.51199871301651},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3450419306755066},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3287208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3287208","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:37335790","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37335790","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":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1498893086","display_name":null,"funder_award_id":"62036012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2037785589","display_name":null,"funder_award_id":"U21B2044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2407878474","display_name":null,"funder_award_id":"62072286","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2454296646","display_name":null,"funder_award_id":"62106262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2908564948","display_name":null,"funder_award_id":"62002355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4100755579","display_name":null,"funder_award_id":"L201001","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G4199693610","display_name":null,"funder_award_id":"62236008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4790433124","display_name":null,"funder_award_id":"62102415","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6431871145","display_name":null,"funder_award_id":"61721004","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":83,"referenced_works":["https://openalex.org/W1927052826","https://openalex.org/W2119031011","https://openalex.org/W2142194269","https://openalex.org/W2336403884","https://openalex.org/W2337252826","https://openalex.org/W2535977253","https://openalex.org/W2619947201","https://openalex.org/W2766402183","https://openalex.org/W2766630207","https://openalex.org/W2810912957","https://openalex.org/W2884293275","https://openalex.org/W2895361760","https://openalex.org/W2948229620","https://openalex.org/W2952435096","https://openalex.org/W2962677524","https://openalex.org/W2962709777","https://openalex.org/W2962876901","https://openalex.org/W2963045696","https://openalex.org/W2963524571","https://openalex.org/W2963919999","https://openalex.org/W2964036161","https://openalex.org/W2970724283","https://openalex.org/W2972712288","https://openalex.org/W2981998043","https://openalex.org/W2983918066","https://openalex.org/W2984619425","https://openalex.org/W2986407524","https://openalex.org/W2988098865","https://openalex.org/W2989042503","https://openalex.org/W2989506443","https://openalex.org/W2990503944","https://openalex.org/W2997706915","https://openalex.org/W2998601171","https://openalex.org/W2998702159","https://openalex.org/W3009148386","https://openalex.org/W3016459781","https://openalex.org/W3034623254","https://openalex.org/W3034687522","https://openalex.org/W3035180180","https://openalex.org/W3035585099","https://openalex.org/W3095669214","https://openalex.org/W3097664769","https://openalex.org/W3100481960","https://openalex.org/W3106041614","https://openalex.org/W3107128832","https://openalex.org/W3109715102","https://openalex.org/W3109986575","https://openalex.org/W3110589170","https://openalex.org/W3112040205","https://openalex.org/W3149230594","https://openalex.org/W3150815828","https://openalex.org/W3168126734","https://openalex.org/W3173212682","https://openalex.org/W3173698268","https://openalex.org/W3173874725","https://openalex.org/W3174421047","https://openalex.org/W3174511093","https://openalex.org/W3175357208","https://openalex.org/W3176212189","https://openalex.org/W3176853098","https://openalex.org/W3178036208","https://openalex.org/W3182120198","https://openalex.org/W3189379416","https://openalex.org/W3189800722","https://openalex.org/W3201832684","https://openalex.org/W3203848195","https://openalex.org/W3207172562","https://openalex.org/W3207758636","https://openalex.org/W3207927851","https://openalex.org/W4214589115","https://openalex.org/W4225505766","https://openalex.org/W4226270831","https://openalex.org/W4226500165","https://openalex.org/W4301963599","https://openalex.org/W4312421085","https://openalex.org/W4312508181","https://openalex.org/W4312578992","https://openalex.org/W4313024697","https://openalex.org/W4386076085","https://openalex.org/W6717697761","https://openalex.org/W6760239191","https://openalex.org/W6793520193","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Weakly-supervised":[0],"temporal":[1,52,75,98,124,147],"action":[2,11,35,56,65,82,136,140],"localization":[3,141],"(WSTAL)":[4],"aims":[5],"to":[6,31,42,46,59,62,90,199],"automatically":[7],"identify":[8],"and":[9,92,97,112,123,138,146,157,228],"localize":[10],"instances":[12],"in":[13,37,154,172,197,211,233],"untrimmed":[14,39],"videos":[15],"with":[16,119],"only":[17],"video-level":[18],"labels":[19],"as":[20,207,209],"supervision.":[21],"In":[22,107,219],"this":[23,108],"task,":[24],"there":[25],"exist":[26],"two":[27,105,166],"challenges:":[28],"(1)":[29],"how":[30,45],"accurately":[32],"discover":[33,63],"the":[34,50,64,95,103,120,144,155,165,187,200,214,226],"categories":[36],"an":[38],"video":[40],"(what":[41],"discover);":[43],"(2)":[44],"elaborately":[47],"focus":[48],"on":[49,182,217],"integral":[51],"interval":[53],"of":[54,213,230],"each":[55,152,231],"instance":[57],"(where":[58],"focus).":[60],"Empirically,":[61],"categories,":[66],"discriminative":[67],"semantic":[68,96,121,145],"information":[69,77,101,150],"should":[70],"be":[71],"extracted,":[72],"while":[73],"robust":[74],"contextual":[76,99,125,148],"is":[78,130,162],"beneficial":[79],"for":[80,102,151],"complete":[81,139],"localization.":[83],"However,":[84],"most":[85],"existing":[86,201],"WSTAL":[87],"methods":[88],"ignore":[89],"explicitly":[91],"jointly":[93],"model":[94],"correlation":[100,126,149],"above":[104],"challenges.":[106],"article,":[109],"a":[110,173],"Semantic":[111],"Temporal":[113],"Contextual":[114],"Correlation":[115],"Learning":[116],"Network":[117],"(STCL-Net)":[118],"(SCL)":[122],"learning":[127],"(TCL)":[128],"modules":[129,168],"proposed,":[131],"which":[132],"achieves":[133],"both":[134,170],"accurate":[135],"discovery":[137],"by":[142],"modeling":[143],"snippet":[153],"inter-":[156],"intra-video":[158],"manners":[159],"respectively.":[160],"It":[161],"noteworthy":[163],"that":[164],"proposed":[167,190],"are":[169,180],"designed":[171],"unified":[174],"dynamic":[175],"correlation-embedding":[176],"paradigm.":[177],"Extensive":[178],"experiments":[179],"performed":[181],"different":[183],"benchmarks.":[184],"On":[185],"all":[186],"benchmarks,":[188],"our":[189,234],"method":[191],"exhibits":[192],"superior":[193],"or":[194],"comparable":[195],"performance":[196],"comparison":[198],"state-of-the-art":[202],"models,":[203],"especially":[204],"achieving":[205],"gains":[206],"high":[208],"7.2%":[210],"terms":[212],"average":[215],"mAP":[216],"THUMOS-14.":[218],"addition,":[220],"comprehensive":[221],"ablation":[222],"studies":[223],"also":[224],"verify":[225],"effectiveness":[227],"robustness":[229],"component":[232],"model.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
