{"id":"https://openalex.org/W4411600835","doi":"https://doi.org/10.1109/tce.2025.3582624","title":"Temporal-Spatial-Relation Former for Multi-Person Motion Prediction","display_name":"Temporal-Spatial-Relation Former for Multi-Person Motion Prediction","publication_year":2025,"publication_date":"2025-06-24","ids":{"openalex":"https://openalex.org/W4411600835","doi":"https://doi.org/10.1109/tce.2025.3582624"},"language":"en","primary_location":{"id":"doi:10.1109/tce.2025.3582624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3582624","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","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/A5100356855","display_name":"Yun Zhang","orcid":"https://orcid.org/0009-0001-0273-7255"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Zhang","raw_affiliation_strings":["School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0001-0273-7255","affiliations":[{"raw_affiliation_string":"School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108881532","display_name":"Chiyu Cai","orcid":"https://orcid.org/0009-0008-2224-2824"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chiyu Cai","raw_affiliation_strings":["Department of Big Data Development, State Information Center, Beijing, China","State Information Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Big Data Development, State Information Center, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"State Information Center, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019787111","display_name":"Xiaoling Luo","orcid":"https://orcid.org/0000-0003-4862-945X"},"institutions":[{"id":"https://openalex.org/I64852412","display_name":"Sichuan University of Science and Engineering","ror":"https://ror.org/053fzma23","country_code":"CN","type":"education","lineage":["https://openalex.org/I64852412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoling Luo","raw_affiliation_strings":["Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things, Sichuan University of Science and Engineering, Yibin, China"],"raw_orcid":"https://orcid.org/0000-0003-4862-945X","affiliations":[{"raw_affiliation_string":"Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things, Sichuan University of Science and Engineering, Yibin, China","institution_ids":["https://openalex.org/I64852412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100614511","display_name":"Ping Li","orcid":"https://orcid.org/0000-0002-8391-6510"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Li","raw_affiliation_strings":["School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-8391-6510","affiliations":[{"raw_affiliation_string":"School of Computer Science and Software Engineering, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062262445","display_name":"Yalan Ye","orcid":"https://orcid.org/0000-0001-5974-1717"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalan Ye","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-5974-1717","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"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":0.11359181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"71","issue":"3","first_page":"8742","last_page":"8751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9922000169754028,"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":0.9922000169754028,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9894000291824341,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9771000146865845,"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/relation","display_name":"Relation (database)","score":0.6839485168457031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5387782454490662},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.52094566822052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.509631872177124},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41700321435928345},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20970302820205688}],"concepts":[{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6839485168457031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5387782454490662},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.52094566822052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.509631872177124},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41700321435928345},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20970302820205688}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2025.3582624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3582624","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2568803418","display_name":null,"funder_award_id":"U2333211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5184646845","display_name":null,"funder_award_id":"2024QHZ031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8265303215","display_name":null,"funder_award_id":"NSFC62276099","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2101032778","https://openalex.org/W2183341477","https://openalex.org/W2802025241","https://openalex.org/W2888934629","https://openalex.org/W2895748257","https://openalex.org/W2898429451","https://openalex.org/W2963065614","https://openalex.org/W2979930345","https://openalex.org/W2982573856","https://openalex.org/W2983925976","https://openalex.org/W3034423770","https://openalex.org/W3045019771","https://openalex.org/W3109717189","https://openalex.org/W3170101352","https://openalex.org/W3174292795","https://openalex.org/W3196571547","https://openalex.org/W3203071852","https://openalex.org/W3205898917","https://openalex.org/W4224289525","https://openalex.org/W4289792177","https://openalex.org/W4307233755","https://openalex.org/W4312272780","https://openalex.org/W4312750092","https://openalex.org/W4319993414","https://openalex.org/W4386071503","https://openalex.org/W4389169911","https://openalex.org/W4390872783","https://openalex.org/W4390873117","https://openalex.org/W4391248741","https://openalex.org/W4392013940","https://openalex.org/W4393148536","https://openalex.org/W4399010425","https://openalex.org/W4402702971","https://openalex.org/W4402715909","https://openalex.org/W4402727169","https://openalex.org/W4407467080","https://openalex.org/W4409365843"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Multi-person":[0],"motion":[1,17,106,136,156],"detection":[2],"remains":[3],"a":[4,66,113,132],"challenging":[5],"problem":[6],"due":[7],"to":[8,99,116],"the":[9,22,30,62,89,93,109,127],"highly":[10],"complex":[11,164],"spatiotemporal":[12,47,77],"dynamics":[13,137],"it":[14],"involves.":[15],"Effective":[16],"forecasting":[18,73],"requires":[19],"capturing":[20,163],"both":[21,76],"internal":[23],"joint":[24],"movement":[25],"patterns":[26],"of":[27,85,105,135],"individuals":[28],"and":[29,78,96,102,123,167],"interactions":[31,53,169],"among":[32],"multiple":[33,139],"individuals.":[34],"While":[35],"existing":[36],"Transformer-based":[37],"models":[38],"have":[39],"demonstrated":[40],"remarkable":[41],"performance,":[42,151],"they":[43],"predominantly":[44],"focus":[45],"on":[46,143],"features,":[48],"often":[49],"neglecting":[50],"crucial":[51],"relational":[52,79,168],"between":[54],"joints.":[55],"To":[56],"address":[57],"this":[58],"limitation,":[59],"we":[60],"propose":[61],"Temporal-Spatial-Relation":[63],"Former":[64],"(TSRFormer),":[65],"novel":[67],"model":[68],"for":[69],"multi-person":[70,171],"3D":[71],"pose":[72],"that":[74,147],"integrates":[75],"features.":[80],"The":[81,141],"proposed":[82,128],"TSRFormer":[83,148],"consists":[84],"two":[86],"complementary":[87],"branches:":[88],"first":[90],"branch":[91,111],"leverages":[92],"Spatial":[94],"Transformer":[95,98],"Temporal":[97],"extract":[100],"spatial":[101],"temporal":[103,165],"dependencies":[104,166],"joints,":[107],"while":[108],"second":[110],"employs":[112],"convolutional":[114],"network":[115],"capture":[117],"inter-person":[118],"relationships.":[119],"These":[120],"branches":[121],"interact":[122],"exchange":[124],"information":[125],"within":[126],"computational":[129],"mode,":[130],"enabling":[131],"holistic":[133],"understanding":[134],"from":[138],"perspectives.":[140],"experiments":[142],"benchmark":[144],"datasets":[145],"demonstrate":[146],"achieves":[149],"competitive":[150],"particularly":[152],"excelling":[153],"in":[154,162,170],"long-term":[155],"prediction,":[157],"thereby":[158],"validating":[159],"its":[160],"effectiveness":[161],"scenarios.":[172]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
