{"id":"https://openalex.org/W4402982574","doi":"https://doi.org/10.1109/icme57554.2024.10688242","title":"Multi-feature and Multi-branch Action Segmentation Framework for Modeling Long-Short-Term Dependencies","display_name":"Multi-feature and Multi-branch Action Segmentation Framework for Modeling Long-Short-Term Dependencies","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402982574","doi":"https://doi.org/10.1109/icme57554.2024.10688242"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10688242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10688242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5012577897","display_name":"Junkun Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junkun Hong","raw_affiliation_strings":["Central South University,School of Computer Science and Engineering,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Computer Science and Engineering,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037210550","display_name":"Yitian Long","orcid":null},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]},{"id":"https://openalex.org/I4210162197","display_name":"Vanderbilt Health","ror":"https://ror.org/05grhsk96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210162197"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yitian Long","raw_affiliation_strings":["Vanderbilt University,Data Science Institute,Nashville,Tennessee,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vanderbilt University,Data Science Institute,Nashville,Tennessee,United States","institution_ids":["https://openalex.org/I4210162197","https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029010292","display_name":"Yueyi Luo","orcid":"https://orcid.org/0000-0002-1516-3457"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueyi Luo","raw_affiliation_strings":["Central South University,School of Mathematics and Statistics,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,School of Mathematics and Statistics,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101620144","display_name":"Qianqian Qi","orcid":"https://orcid.org/0000-0003-1058-476X"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianqian Qi","raw_affiliation_strings":["Central South University,Big Data Institution,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,Big Data Institution,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101607089","display_name":"Jun Long","orcid":"https://orcid.org/0000-0002-2773-1773"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Long","raw_affiliation_strings":["Central South University,Big Data Institution,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,Big Data Institution,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3055,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65188259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.822700023651123,"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":0.822700023651123,"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/T12127","display_name":"Software System Performance and Reliability","score":0.7864000201225281,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.6922000050544739,"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/computer-science","display_name":"Computer science","score":0.7249940633773804},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.7046202421188354},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.614905834197998},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5467185378074646},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5225231647491455},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4646299481391907},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3662912845611572}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7249940633773804},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.7046202421188354},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.614905834197998},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5467185378074646},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5225231647491455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4646299481391907},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3662912845611572},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10688242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10688242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2031688197","https://openalex.org/W2099614498","https://openalex.org/W2109698606","https://openalex.org/W2550143307","https://openalex.org/W2963524571","https://openalex.org/W2963853051","https://openalex.org/W3083550439","https://openalex.org/W3119038403","https://openalex.org/W3204193736","https://openalex.org/W4225271941","https://openalex.org/W4283834781","https://openalex.org/W4312322722","https://openalex.org/W4312337393","https://openalex.org/W4312753781","https://openalex.org/W4312982010","https://openalex.org/W4372263459","https://openalex.org/W4375869475","https://openalex.org/W4379927854","https://openalex.org/W4385767495","https://openalex.org/W4386076622","https://openalex.org/W4386076624","https://openalex.org/W4386172434","https://openalex.org/W4387969575","https://openalex.org/W4390970721","https://openalex.org/W4393046558","https://openalex.org/W6855980909"],"related_works":["https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W2330575325","https://openalex.org/W2163803519","https://openalex.org/W2497592525","https://openalex.org/W3096145648","https://openalex.org/W3197510923","https://openalex.org/W2370579019","https://openalex.org/W4313265328","https://openalex.org/W4386159726"],"abstract_inverted_index":{"Pioneer":[0],"efforts":[1],"have":[2,51],"been":[3],"dedicated":[4],"to":[5,64,96,139],"action":[6,56,81],"segmentation":[7,57,82],"that":[8],"predicts":[9],"what":[10],"step":[11],"is":[12,136],"occurring":[13],"in":[14,55,127],"a":[15,77,93,103],"video":[16,26,99],"frame.":[17],"Existing":[18],"studies":[19],"focus":[20],"on":[21],"improving":[22],"the":[23,30,70],"accuracy":[24],"of":[25,33,38],"segmentation,":[27],"but":[28,59],"neglect":[29],"temporal":[31,98],"continuity":[32],"intersegments":[34],"and":[35,68,79,87,101,110,120,129],"semantic":[36],"consistency":[37],"intra-segments,":[39],"which":[40,132],"are":[41],"necessary":[42],"for":[43,84,106],"developing":[44],"computer-assisted":[45,140],"systems.":[46,141],"Meanwhile,":[47],"Temporal":[48],"Convolutional":[49],"Networks":[50],"shown":[52],"good":[53],"performance":[54],"tasks,":[58],"their":[60],"high":[61],"layers":[62],"tend":[63],"lose":[65],"fine-grained":[66],"information":[67],"impact":[69],"results.":[71],"Toward":[72],"this":[73],"end,":[74],"we":[75,91],"devise":[76],"multi-feature":[78,94],"multi-branch":[80,104],"framework":[83,116,135],"modeling":[85],"long-term":[86],"short-term":[88],"dependencies.":[89],"Specifically,":[90],"present":[92],"fusion":[95],"enhance":[97],"representation":[100],"design":[102],"predictor":[105],"extracting":[107],"both":[108],"segment-level":[109],"frame-level":[111],"information.":[112],"We":[113],"justify":[114],"our":[115,134],"over":[117],"three":[118],"datasets":[119],"experimental":[121],"results":[122],"demonstrate":[123],"its":[124],"superiority,":[125],"especially":[126],"Edit":[128],"F1":[130],"metrics,":[131],"means":[133],"more":[137],"applicable":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
