{"id":"https://openalex.org/W4415709503","doi":"https://doi.org/10.1109/icme59968.2025.11209846","title":"Multi-Scale Hypergraph Relational Reasoning for Weakly Supervised Recognition of Group Activities","display_name":"Multi-Scale Hypergraph Relational Reasoning for Weakly Supervised Recognition of Group Activities","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415709503","doi":"https://doi.org/10.1109/icme59968.2025.11209846"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5075769692","display_name":"Chongyang Xu","orcid":"https://orcid.org/0000-0001-7431-6540"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongyang Xu","raw_affiliation_strings":["College of Computer Science, Sichuan University,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034974804","display_name":"Runtian Zheng","orcid":"https://orcid.org/0000-0001-5158-1165"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runtian Zheng","raw_affiliation_strings":["College of Computer Science, Sichuan University,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031943397","display_name":"Ziliang Feng","orcid":"https://orcid.org/0000-0001-6484-7612"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziliang Feng","raw_affiliation_strings":["College of Computer Science, Sichuan University,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101577714","display_name":"Chengfang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengfang Zhang","raw_affiliation_strings":["Intelligent Policing Key Laboratory of Sichuan Province, Sichuan Police College,Luzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Policing Key Laboratory of Sichuan Province, Sichuan Police College,Luzhou,China","institution_ids":["https://openalex.org/I4210147983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.28241249,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.8532999753952026,"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":0.8532999753952026,"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":0.01590000092983246,"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":0.014700000174343586,"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/hypergraph","display_name":"Hypergraph","score":0.644599974155426},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5512999892234802},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5073000192642212},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42649999260902405},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4212000072002411},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.41029998660087585},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.35089999437332153}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6462000012397766},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.644599974155426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6194999814033508},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5512999892234802},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5073000192642212},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3203999996185303},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.31690001487731934},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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":29,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2259801182","https://openalex.org/W2736442062","https://openalex.org/W2766629694","https://openalex.org/W2892880750","https://openalex.org/W2927778007","https://openalex.org/W2940963663","https://openalex.org/W2963150697","https://openalex.org/W3035029089","https://openalex.org/W3035648302","https://openalex.org/W3096609285","https://openalex.org/W3096719817","https://openalex.org/W3108614371","https://openalex.org/W3110257409","https://openalex.org/W3135677014","https://openalex.org/W3200394086","https://openalex.org/W3204485253","https://openalex.org/W4230451144","https://openalex.org/W4282926996","https://openalex.org/W4293519341","https://openalex.org/W4312557989","https://openalex.org/W4312858532","https://openalex.org/W4312919330","https://openalex.org/W4313229717","https://openalex.org/W4313291202","https://openalex.org/W4379794219","https://openalex.org/W4387171776","https://openalex.org/W4390874237","https://openalex.org/W4402979967"],"related_works":[],"abstract_inverted_index":{"Group":[0],"activity":[1,74,124],"recognition":[2],"in":[3,40,49],"weakly":[4,71],"supervised":[5,72],"settings":[6],"can":[7],"be":[8],"approached":[9],"through":[10,114,151],"either":[11],"detector-based":[12],"or":[13],"detector-free":[14,45],"methods.":[15],"Detector-based":[16],"methods":[17,46,78],"typically":[18],"rely":[19],"on":[20,161],"predefined":[21],"graph":[22,81],"structures":[23],"to":[24,32,87,135],"capture":[25,88],"group":[26,41,73,137],"relationships,":[27],"which":[28],"limits":[29],"their":[30],"ability":[31],"model":[33],"the":[34,127,162],"dynamic,":[35],"multi-scale,":[36],"and":[37,54,92,106,109,118,147,166],"fine-grained":[38,144],"changes":[39],"interactions.":[42],"In":[43,57],"contrast,":[44],"face":[47],"challenges":[48],"effectively":[50,141],"filtering":[51],"irrelevant":[52],"background":[53],"spectator":[55],"information.":[56],"this":[58],"paper,":[59],"we":[60],"propose":[61],"a":[62],"novel":[63],"multi-scale":[64,129,154],"hypergraph":[65],"neural":[66],"network":[67],"framework,":[68],"MHGAR,":[69],"for":[70],"recognition.":[75],"Unlike":[76],"traditional":[77],"with":[79,131],"fixed":[80],"structures,":[82],"MHGAR":[83],"dynamically":[84],"constructs":[85],"hyperedges":[86],"complex":[89],"team":[90,149],"formations":[91,150],"sub-group":[93,145],"interactions":[94,146],"at":[95],"multiple":[96],"scales.":[97],"We":[98],"initialize":[99],"player":[100],"representations":[101,113],"by":[102],"combining":[103],"visual":[104],"appearance":[105],"spatial":[107],"positions,":[108],"iteratively":[110],"refine":[111],"these":[112],"dynamic":[115],"hyperedge":[116],"construction":[117],"bi-directional":[119],"message":[120],"passing.":[121],"A":[122],"cross-attentive":[123],"classifier":[125],"integrates":[126],"refined":[128],"features":[130],"ball":[132],"position":[133],"information":[134],"predict":[136],"activities.":[138],"Our":[139],"method":[140],"captures":[142],"both":[143],"high-level":[148],"its":[152],"adaptive":[153],"modeling.":[155],"Experimental":[156],"results":[157],"demonstrate":[158],"state-of-the-art":[159],"performance":[160],"widely":[163],"used":[164],"Volleyball":[165],"NBA":[167],"datasets.":[168]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-30T00:00:00"}