{"id":"https://openalex.org/W4402125445","doi":"https://doi.org/10.1109/tmm.2024.3452980","title":"SMC-NCA: Semantic-Guided Multi-Level Contrast for Semi-Supervised Temporal Action Segmentation","display_name":"SMC-NCA: Semantic-Guided Multi-Level Contrast for Semi-Supervised Temporal Action Segmentation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402125445","doi":"https://doi.org/10.1109/tmm.2024.3452980"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2024.3452980","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2024.3452980","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":"https://openalex.org/A5025874707","display_name":"Feixiang Zhou","orcid":"https://orcid.org/0000-0003-4939-9393"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Feixiang Zhou","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","School of Computing and Mathematical Sciences, University of Leicester, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-4939-9393","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]},{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, United Kingdom","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009437198","display_name":"Zheheng Jiang","orcid":"https://orcid.org/0000-0003-1401-7615"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zheheng Jiang","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","School of Computing and Mathematical Sciences, University of Leicester, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-1401-7615","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]},{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, United Kingdom","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066119228","display_name":"Huiyu Zhou","orcid":"https://orcid.org/0000-0003-1634-9840"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huiyu Zhou","raw_affiliation_strings":["School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","School of Computing and Mathematical Sciences, University of Leicester, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-1634-9840","affiliations":[{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K","institution_ids":["https://openalex.org/I153648349"]},{"raw_affiliation_string":"School of Computing and Mathematical Sciences, University of Leicester, United Kingdom","institution_ids":["https://openalex.org/I153648349"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x0027;an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x0027;an, P.R. China"],"raw_orcid":"https://orcid.org/0000-0003-2924-946X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x0027;an, P.R. China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3252,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52932322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"26","issue":null,"first_page":"11386","last_page":"11401"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.8537055253982544},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6071157455444336},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5896360278129578},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5838522911071777},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4559817910194397},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.42462819814682007},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3666099011898041},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32990509271621704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8537055253982544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6071157455444336},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5896360278129578},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5838522911071777},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4559817910194397},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42462819814682007},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3666099011898041},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32990509271621704},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2024.3452980","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2024.3452980","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":[{"display_name":"Reduced inequalities","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W2007964100","https://openalex.org/W2014914041","https://openalex.org/W2031688197","https://openalex.org/W2096733369","https://openalex.org/W2099614498","https://openalex.org/W2109698606","https://openalex.org/W2166083072","https://openalex.org/W2314362175","https://openalex.org/W2461621749","https://openalex.org/W2550143307","https://openalex.org/W2768202427","https://openalex.org/W2798345491","https://openalex.org/W2895347732","https://openalex.org/W2948173315","https://openalex.org/W2951906878","https://openalex.org/W2963524571","https://openalex.org/W2963697717","https://openalex.org/W2963853051","https://openalex.org/W2964159205","https://openalex.org/W2982335217","https://openalex.org/W2983918066","https://openalex.org/W3009622574","https://openalex.org/W3034373833","https://openalex.org/W3034687522","https://openalex.org/W3034802267","https://openalex.org/W3034999503","https://openalex.org/W3035160371","https://openalex.org/W3035524453","https://openalex.org/W3035557275","https://openalex.org/W3083550439","https://openalex.org/W3084758420","https://openalex.org/W3096383329","https://openalex.org/W3108655343","https://openalex.org/W3110264553","https://openalex.org/W3119038403","https://openalex.org/W3128138976","https://openalex.org/W3136965813","https://openalex.org/W3145385912","https://openalex.org/W3158278463","https://openalex.org/W3158661000","https://openalex.org/W3164497174","https://openalex.org/W3168371806","https://openalex.org/W3171349866","https://openalex.org/W3174700686","https://openalex.org/W3174889475","https://openalex.org/W3180945712","https://openalex.org/W3187068415","https://openalex.org/W3190152617","https://openalex.org/W3199148273","https://openalex.org/W3201942032","https://openalex.org/W3202074654","https://openalex.org/W3210314917","https://openalex.org/W3215811789","https://openalex.org/W3217228024","https://openalex.org/W4200633745","https://openalex.org/W4210915468","https://openalex.org/W4214507759","https://openalex.org/W4226017838","https://openalex.org/W4226177518","https://openalex.org/W4292829079","https://openalex.org/W4312337393","https://openalex.org/W4312626235","https://openalex.org/W4313165677","https://openalex.org/W4364353722","https://openalex.org/W4379927854","https://openalex.org/W4386050422","https://openalex.org/W4386075981","https://openalex.org/W4388286388","https://openalex.org/W4390872217","https://openalex.org/W4390872435","https://openalex.org/W4391321196","https://openalex.org/W6733814495","https://openalex.org/W6759891849","https://openalex.org/W6773005947","https://openalex.org/W6779977557","https://openalex.org/W6788329692","https://openalex.org/W6791353385","https://openalex.org/W6795951589","https://openalex.org/W6802442395","https://openalex.org/W6841660130","https://openalex.org/W6843938134","https://openalex.org/W6844194202","https://openalex.org/W6845728527","https://openalex.org/W6850726482"],"related_works":["https://openalex.org/W2069592018","https://openalex.org/W2075740387","https://openalex.org/W2358990940","https://openalex.org/W2093931120","https://openalex.org/W2329812990","https://openalex.org/W2349116365","https://openalex.org/W3021708704","https://openalex.org/W2004231473","https://openalex.org/W2060895226","https://openalex.org/W2151991951"],"abstract_inverted_index":{"Semi-supervised":[0],"temporal":[1,111],"action":[2,54],"segmentation":[3,55,177],"(SS-TAS)":[4],"aims":[5],"to":[6,78,93,134,159],"perform":[7],"frame-wise":[8,81],"classification":[9],"in":[10,20,35,99,174,179],"long":[11],"untrimmed":[12],"videos,":[13],"where":[14],"only":[15,183],"a":[16,67,74,100],"fraction":[17],"of":[18,32,46,157,163,182,193],"videos":[19],"the":[21,30,44,118,148,170,180,189,194],"training":[22],"set":[23],"have":[24,28],"labels.":[25],"Recent":[26],"studies":[27],"shown":[29],"potential":[31],"contrastive":[33,51,103],"learning":[34,38,43,52,143],"unsupervised":[36,50],"representation":[37,45,87],"using":[39],"unlabelled":[40],"data.":[41],"However,":[42],"each":[47],"frame":[48],"by":[49],"for":[53,83,86,124,141],"remains":[56],"an":[57],"open":[58],"and":[59,96,102,110,166,191],"challenging":[60],"problem.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"propose":[66],"novel":[68],"Semantic-guided":[69],"Multi-level":[70],"Contrast":[71],"scheme":[72],"with":[73],"Neighbourhood-Consistency-Aware":[75],"unit":[76,172],"(SMC-NCA)":[77],"extract":[79],"strong":[80],"representations":[82],"SS-TAS.":[84],"Specifically,":[85],"learning,":[88],"SMC":[89,140,146],"is":[90,122],"first":[91],"used":[92],"explore":[94],"intra-":[95],"inter-information":[97],"variations":[98],"unified":[101],"way,":[104],"based":[105],"on":[106,152,197],"action-specific":[107],"semantic":[108],"information":[109,112],"highlighting":[113],"relations":[114],"between":[115,128],"actions.":[116],"Then,":[117],"NCA":[119,171],"module,":[120],"which":[121],"responsible":[123],"enforcing":[125],"spatial":[126],"consistency":[127],"neighbourhoods":[129],"centered":[130],"at":[131],"different":[132],"frames":[133],"alleviate":[135],"over-segmentation":[136],"issues,":[137],"works":[138],"alongside":[139],"semi-supervised":[142],"(SSL).":[144],"Our":[145],"outperforms":[147],"other":[149],"state-of-the-art":[150],"methods":[151],"three":[153],"benchmarks,":[154],"offering":[155],"improvements":[156],"up":[158],"17.8$\\%$and":[160],"12.6$\\%$in":[161],"terms":[162],"Edit":[164],"distance":[165],"accuracy,":[167],"respectively.":[168],"Additionally,":[169],"results":[173],"significantly":[175],"better":[176],"performance":[178],"presence":[181],"5$\\%$labelled":[184],"videos.":[185],"We":[186],"also":[187],"demonstrate":[188],"generalizability":[190],"effectiveness":[192],"proposed":[195],"method":[196],"our":[198],"Parkinson's":[199],"Disease":[200],"Mouse":[201],"Behaviour":[202],"(PDMB)":[203],"dataset.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
