{"id":"https://openalex.org/W4413469167","doi":"https://doi.org/10.1109/tmm.2025.3599049","title":"Relation Learning and Aggregate-Attention for Multi-Person Motion Prediction","display_name":"Relation Learning and Aggregate-Attention for Multi-Person Motion Prediction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413469167","doi":"https://doi.org/10.1109/tmm.2025.3599049"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3599049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3599049","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/A5101336683","display_name":"Kehua Qu","orcid":"https://orcid.org/0009-0008-0319-3131"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kehua Qu","raw_affiliation_strings":["Information Engineering College, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-0319-3131","affiliations":[{"raw_affiliation_string":"Information Engineering College, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102859092","display_name":"Rui Ding","orcid":"https://orcid.org/0000-0002-4591-1065"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Ding","raw_affiliation_strings":["Information Engineering College, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4591-1065","affiliations":[{"raw_affiliation_string":"Information Engineering College, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033216492","display_name":"Jin Tang","orcid":"https://orcid.org/0000-0001-9065-4021"},"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":"Jin Tang","raw_affiliation_strings":["School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9065-4021","affiliations":[{"raw_affiliation_string":"School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7655,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74091546,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"27","issue":null,"first_page":"7215","last_page":"7229"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980999827384949,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980999827384949,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9890999794006348,"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/computer-science","display_name":"Computer science","score":0.8085087537765503},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7036787271499634},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.6892330646514893},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5551227331161499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5356796383857727},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4771411120891571},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.30095863342285156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8085087537765503},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7036787271499634},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.6892330646514893},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5551227331161499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5356796383857727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4771411120891571},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30095863342285156},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3599049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3599049","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2101032778","https://openalex.org/W2606517404","https://openalex.org/W2888934629","https://openalex.org/W2891091472","https://openalex.org/W2895748257","https://openalex.org/W2971856312","https://openalex.org/W2982573856","https://openalex.org/W2983925976","https://openalex.org/W2991653934","https://openalex.org/W3034423770","https://openalex.org/W3036644940","https://openalex.org/W3045019771","https://openalex.org/W3107320732","https://openalex.org/W3109597949","https://openalex.org/W3109717189","https://openalex.org/W3170101352","https://openalex.org/W3176882544","https://openalex.org/W3203071852","https://openalex.org/W3203785074","https://openalex.org/W3205898917","https://openalex.org/W3215117597","https://openalex.org/W3215686035","https://openalex.org/W4225557002","https://openalex.org/W4230178929","https://openalex.org/W4283377921","https://openalex.org/W4285069978","https://openalex.org/W4285254909","https://openalex.org/W4306955484","https://openalex.org/W4312750092","https://openalex.org/W4312774977","https://openalex.org/W4313041951","https://openalex.org/W4313229717","https://openalex.org/W4323795150","https://openalex.org/W4367663575","https://openalex.org/W4383172020","https://openalex.org/W4383220221","https://openalex.org/W4385257474","https://openalex.org/W4385767582","https://openalex.org/W4386065605","https://openalex.org/W4386071503","https://openalex.org/W4386076301","https://openalex.org/W4388283673","https://openalex.org/W4389169911","https://openalex.org/W4389298891","https://openalex.org/W4390872783","https://openalex.org/W4394625779","https://openalex.org/W4402716188"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2323648130","https://openalex.org/W2157140558","https://openalex.org/W2378782423","https://openalex.org/W2388988621","https://openalex.org/W2357797405","https://openalex.org/W2366623913","https://openalex.org/W2374905595","https://openalex.org/W2516693588","https://openalex.org/W2116112408"],"abstract_inverted_index":{"Multi-person":[0],"motion":[1,16,76],"prediction":[2,77],"is":[3],"an":[4,131],"emerging":[5],"and":[6,54,88],"intricate":[7],"task":[8],"with":[9],"broad":[10],"real-world":[11],"applications.":[12],"Unlike":[13],"single":[14],"person":[15],"prediction,":[17],"it":[18],"considers":[19],"not":[20],"just":[21],"the":[22,30,45,124,142,155],"skeleton":[23],"structures":[24],"or":[25],"human":[26],"trajectories":[27],"but":[28,42],"also":[29,145],"interactions":[31,55],"between":[32],"others.":[33],"Previous":[34],"methods":[35],"achieve":[36],"impressive":[37],"predictions":[38],"using":[39],"various":[40],"networks":[41],"often":[43],"overlook":[44],"distinct":[46],"representations":[47],"of":[48],"joint":[49],"relations":[50],"within":[51],"individuals":[52],"(intra-relations)":[53],"among":[56],"groups":[57],"(inter-relations),":[58],"inevitably":[59],"leading":[60],"to":[61,134,148],"undesired":[62],"dependencies.":[63],"To":[64],"address":[65],"this":[66],"issue,":[67],"we":[68,96,116],"introduce":[69],"a":[70,83,89,98,110,118],"new":[71],"collaborative":[72],"framework":[73],"for":[74,86,93],"multi-person":[75],"that":[78,101,141,174],"explicitly":[79],"modeling":[80],"these":[81,137],"relations:":[82],"GCN-based":[84],"network":[85,92],"intra-relations":[87],"novel":[90,119],"reasoning":[91],"inter-relations.":[94],"Specifically,":[95],"propose":[97,117],"distance-aware":[99],"cross-attention":[100],"incorporates":[102],"physical":[103],"distance":[104,112],"constraints":[105],"into":[106],"inter-relation":[107],"learning":[108],"through":[109],"learnable":[111],"weighting":[113],"coefficient.":[114],"Moreover,":[115],"plug-and-play":[120],"aggregation":[121],"module":[122,143],"called":[123],"Interaction":[125],"Aggregation":[126],"Module":[127],"(IAM),":[128],"which":[129],"employs":[130],"aggregate-attention":[132],"mechanism":[133],"seamlessly":[135],"integrate":[136],"relations.":[138],"Experiments":[139],"indicate":[140],"can":[144],"be":[146],"applied":[147],"other":[149],"dual-path":[150],"models.":[151],"Extensive":[152],"experiments":[153],"on":[154],"3DPW,":[156],"3DPW-RC,":[157],"CMU-Mocap,":[158],"MuPoTS-3D,":[159],"as":[160,162],"well":[161],"synthesized":[163],"datasets":[164],"Mix1":[165],"&":[166],"Mix2":[167],"(9<inline-formula":[168],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[169],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[170],"notation=\"LaTeX\">$\\sim$</tex-math></inline-formula>15":[171],"persons),":[172],"demonstrate":[173],"our":[175],"method":[176],"achieves":[177],"state-of-the-art":[178],"performance.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}