{"id":"https://openalex.org/W7138264375","doi":"https://doi.org/10.1609/aaai.v40i6.42491","title":"Breaking the Passive Learning Trap: An Active Perception Strategy for Human Motion Prediction","display_name":"Breaking the Passive Learning Trap: An Active Perception Strategy for Human Motion Prediction","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138264375","doi":"https://doi.org/10.1609/aaai.v40i6.42491"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i6.42491","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42491","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42491/46452","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42491/46452","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129723466","display_name":"Juncheng Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210136497","display_name":"Jilin Medical University","ror":"https://ror.org/03mzw7781","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juncheng Hu","raw_affiliation_strings":["Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210136497"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129751628","display_name":"Zijian Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210136497","display_name":"Jilin Medical University","ror":"https://ror.org/03mzw7781","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijian Zhang","raw_affiliation_strings":["Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210136497"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129724903","display_name":"Zeyu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I61565387","display_name":"Dalian Minzu University","ror":"https://ror.org/02hxfx521","country_code":"CN","type":"education","lineage":["https://openalex.org/I61565387"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeyu Wang","raw_affiliation_strings":["Dalian Minzu University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian Minzu University","institution_ids":["https://openalex.org/I61565387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129693844","display_name":"Guoyu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210136497","display_name":"Jilin Medical University","ror":"https://ror.org/03mzw7781","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoyu Wang","raw_affiliation_strings":["Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210136497"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129647457","display_name":"Yingji Li","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210136497","display_name":"Jilin Medical University","ror":"https://ror.org/03mzw7781","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingji Li","raw_affiliation_strings":["Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210136497"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086502379","display_name":"Kedi Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210136497","display_name":"Jilin Medical University","ror":"https://ror.org/03mzw7781","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kedi Lyu","raw_affiliation_strings":["Jilin University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin University","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210136497"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"6","first_page":"4878","last_page":"4886"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.7177000045776367,"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":0.7177000045776367,"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/T12290","display_name":"Human Motion and Animation","score":0.21979999542236328,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12740","display_name":"Gait Recognition and Analysis","score":0.010999999940395355,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/active-perception","display_name":"Active perception","score":0.6226999759674072},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5690000057220459},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.42910000681877136},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.36910000443458557},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3522999882698059},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.34869998693466187},{"id":"https://openalex.org/keywords/humanoid-robot","display_name":"Humanoid robot","score":0.3409000039100647},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.335999995470047},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.32679998874664307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7001000046730042},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.6226999759674072},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5690000057220459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5343999862670898},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.36910000443458557},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3522999882698059},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.3409000039100647},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30709999799728394},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.30559998750686646},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.27630001306533813},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2630000114440918},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i6.42491","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42491","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42491/46452","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/42491","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/42491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i6.42491","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42491","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42491/46452","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2401970690","display_name":null,"funder_award_id":"2024YFB3310200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320322174","display_name":"People's Government of Jilin Province","ror":"https://ror.org/02fzqav45"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138264375.pdf","grobid_xml":"https://content.openalex.org/works/W7138264375.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Forecasting":[0],"3D":[1,45],"human":[2,14,68],"motion":[3,31,69,78,105,133],"is":[4,170,182],"an":[5,62],"important":[6],"embodiment":[7],"of":[8,13,27],"fine-grained":[9],"understanding":[10],"and":[11,30,43,115,127,175,185,220],"cognition":[12],"behavior":[15],"by":[16,210],"artificial":[17],"agents.":[18],"Current":[19],"approaches":[20],"excessively":[21],"rely":[22],"on":[23,214,217,222],"implicit":[24],"network":[25,140,169],"modeling":[26],"spatiotemporal":[28],"relationships":[29],"characteristics,":[32],"falling":[33],"into":[34,100],"the":[35,101,204],"passive":[36],"learning":[37,54,83,168],"trap":[38],"that":[39,97,143,200],"results":[40,198],"in":[41],"redundant":[42],"monotonous":[44],"coordinate":[46,108],"information":[47],"acquisition":[48],"while":[49,80],"lacking":[50],"actively":[51,144,173],"guided":[52],"explicit":[53],"mechanisms.":[55],"To":[56],"overcome":[57],"these":[58],"issues,":[59],"we":[60,90,137],"propose":[61],"Active":[63],"Perceptual":[64],"Strategy":[65],"(APS)":[66],"for":[67,131],"prediction,":[70],"leveraging":[71],"quotient":[72,102],"space":[73],"representations":[74],"to":[75,85,160,172,193],"explicitly":[76],"encode":[77],"properties":[79],"introducing":[81],"auxiliary":[82,162,167],"objectives":[84],"strengthen":[86],"spatio-temporal":[87,146],"modeling.":[88],"Specifically,":[89],"first":[91],"design":[92],"a":[93,139],"data":[94],"perception":[95,141],"module":[96,119,142,152],"projects":[98],"poses":[99],"space,":[103],"decoupling":[104],"geometry":[106],"from":[107,177],"redundancy.":[109],"By":[110],"jointly":[111],"encoding":[112],"tangent":[113],"vectors":[114],"Grassmann":[116],"projections,":[117],"this":[118],"simultaneously":[120],"achieves":[121,203],"geometric":[122],"dimension":[123],"reduction,":[124],"semantic":[125],"decoupling,":[126],"dynamic":[128],"constraint":[129],"enforcement":[130],"effective":[132],"pose":[134],"characterization.":[135],"Furthermore,":[136],"introduce":[138],"learns":[145],"dependencies":[147],"through":[148],"restorative":[149],"learning.":[150],"This":[151],"deliberately":[153],"masks":[154],"specific":[155],"joints":[156],"or":[157],"injects":[158],"noise":[159],"construct":[161],"supervision":[163],"signals.":[164],"A":[165],"dedicated":[166],"designed":[171],"adapt":[174],"learn":[176],"perturbed":[178],"information.":[179],"Notably,":[180],"APS":[181],"model":[183],"agnostic":[184],"can":[186],"be":[187],"integrated":[188],"with":[189],"different":[190],"prediction":[191],"models":[192],"enhance":[194],"active":[195],"perceptual.The":[196],"experimental":[197],"demonstrate":[199],"our":[201],"method":[202],"new":[205],"state-of-the-art,":[206],"outperforming":[207],"existing":[208],"methods":[209],"large":[211],"margins:":[212],"16.3%":[213],"H3.6M,":[215],"13.9%":[216],"CMU":[218],"Mocap,":[219],"10.1%":[221],"3DPW.":[223]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-03-18T00:00:00"}
