{"id":"https://openalex.org/W4391129922","doi":"https://doi.org/10.1109/ic-nidc59918.2023.10390711","title":"Skeleton Based Graph Convolutional Network Method for Action Recognition in Sports: A Review","display_name":"Skeleton Based Graph Convolutional Network Method for Action Recognition in Sports: A Review","publication_year":2023,"publication_date":"2023-11-03","ids":{"openalex":"https://openalex.org/W4391129922","doi":"https://doi.org/10.1109/ic-nidc59918.2023.10390711"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc59918.2023.10390711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc59918.2023.10390711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 8th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"},"type":"review","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/A5109771600","display_name":"Jiangning Wei","orcid":"https://orcid.org/0009-0000-2662-8996"},"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":true,"raw_author_name":"Jiangning Wei","raw_affiliation_strings":["Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071476224","display_name":"Bo Yu","orcid":"https://orcid.org/0000-0002-0347-0927"},"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":"Bo Yu","raw_affiliation_strings":["Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100397026","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0003-1991-119X"},"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":"Hao Zhang","raw_affiliation_strings":["Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100361885","display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-5815-2483"},"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":"Jun Liu","raw_affiliation_strings":["Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Institution of Artificial Intelligence, Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109771600"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.7371,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74020466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9912999868392944,"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":0.972000002861023,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.7685708999633789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7536356449127197},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6173592209815979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.569832980632782},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5659372210502625},{"id":"https://openalex.org/keywords/skeleton","display_name":"Skeleton (computer programming)","score":0.5628648400306702},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47234880924224854},{"id":"https://openalex.org/keywords/power-graph-analysis","display_name":"Power graph analysis","score":0.46971482038497925},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.45011553168296814},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4132181406021118},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40335798263549805},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2969914674758911},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11237993836402893}],"concepts":[{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.7685708999633789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7536356449127197},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6173592209815979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.569832980632782},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5659372210502625},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.5628648400306702},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47234880924224854},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.46971482038497925},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.45011553168296814},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4132181406021118},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40335798263549805},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2969914674758911},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11237993836402893},{"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/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic-nidc59918.2023.10390711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc59918.2023.10390711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 8th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2027150542","https://openalex.org/W2736544854","https://openalex.org/W2940457086","https://openalex.org/W2948058585","https://openalex.org/W2948246283","https://openalex.org/W2963076818","https://openalex.org/W2996249958","https://openalex.org/W3006529527","https://openalex.org/W3018726990","https://openalex.org/W3035050855","https://openalex.org/W3035225512","https://openalex.org/W3092336341","https://openalex.org/W3093441220","https://openalex.org/W3108496296","https://openalex.org/W3174836262","https://openalex.org/W4221001776","https://openalex.org/W4230178929","https://openalex.org/W4296438114","https://openalex.org/W4312591085","https://openalex.org/W6773520705","https://openalex.org/W6799203325"],"related_works":["https://openalex.org/W2953562271","https://openalex.org/W4293226380","https://openalex.org/W2334655667","https://openalex.org/W2964954556","https://openalex.org/W4303411729","https://openalex.org/W4211202157","https://openalex.org/W4399611050","https://openalex.org/W2999049608","https://openalex.org/W3170431411","https://openalex.org/W4391129922"],"abstract_inverted_index":{"Human":[0],"action":[1,29,57,79,98,120],"recognition":[2,121],"has":[3,10],"gained":[4],"significant":[5],"attention":[6],"and":[7,44,53,91,107,116,122],"skeleton-based":[8,63,75,97],"methods":[9,77,85],"become":[11],"a":[12,68,87],"hot":[13],"research":[14,130],"topic":[15],"owning":[16],"to":[17,20],"its":[18],"resilience":[19],"environmental":[21],"variations.":[22],"Graph":[23],"Convolutional":[24],"Networks":[25],"(GCN)":[26],"have":[27],"improved":[28],"recog-nition":[30],"accuracy":[31],"by":[32],"operating":[33],"graph":[34],"convolution":[35],"on":[36,51,86],"graph-structured":[37],"data,":[38],"surpassing":[39],"conventional":[40],"models":[41],"like":[42],"CNN":[43,52],"RNN.":[45],"However,":[46],"current":[47],"works":[48,131],"primarily":[49],"relies":[50],"RNN":[54],"for":[55,78,96],"sport":[56,89,119],"recognition,":[58],"with":[59],"limited":[60],"explo-ration":[61],"of":[62,71,74],"GCN":[64,76],"methods.This":[65],"paper":[66],"provides":[67],"comprehensive":[69],"review":[70],"the":[72],"development":[73],"recognition.":[80],"Additionally,":[81],"we":[82,113],"evaluate":[83],"these":[84],"fine-grained":[88],"dataset":[90],"identify":[92],"three":[93],"crucial":[94],"considerations":[95],"recognition:":[99],"incorporating":[100],"sport-specific":[101],"local":[102],"actions,":[103],"utilizing":[104],"skeleton":[105],"angles,":[106],"designing":[108],"multi-scale":[109],"network":[110],"structures.":[111],"Furthermore,":[112],"highlight":[114],"challenges":[115],"oppor-tunities":[117],"in":[118,132],"hope":[123],"our":[124],"work":[125],"would":[126],"inspire":[127],"more":[128],"excellent":[129],"this":[133],"area.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2026-02-25T23:00:34.991745","created_date":"2025-10-10T00:00:00"}