{"id":"https://openalex.org/W4417073349","doi":"https://doi.org/10.1145/3743093.3771076","title":"A Robust 3D CNN with Pyramidal Attention for Spatiotemporal Gait Recognition","display_name":"A Robust 3D CNN with Pyramidal Attention for Spatiotemporal Gait Recognition","publication_year":2025,"publication_date":"2025-12-06","ids":{"openalex":"https://openalex.org/W4417073349","doi":"https://doi.org/10.1145/3743093.3771076"},"language":null,"primary_location":{"id":"doi:10.1145/3743093.3771076","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3743093.3771076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Multimedia in Asia","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":null,"display_name":"Jianyu Chen","orcid":"https://orcid.org/0000-0002-6784-3809"},"institutions":[{"id":"https://openalex.org/I174442536","display_name":"South Central Minzu University","ror":"https://ror.org/03d7sax13","country_code":"CN","type":"education","lineage":["https://openalex.org/I174442536"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianyu Chen","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, Wuhan University, Whuan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, Wuhan University, Whuan, China","institution_ids":["https://openalex.org/I174442536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101427256","display_name":"Qian Zhou","orcid":"https://orcid.org/0000-0001-7964-8130"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Zhou","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070093927","display_name":"Qin Zou","orcid":"https://orcid.org/0000-0001-7955-0782"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Zou","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748496","display_name":"Chao Liang","orcid":"https://orcid.org/0000-0002-8287-8655"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Liang","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034458344","display_name":"Zengmin Xu","orcid":"https://orcid.org/0000-0002-8934-9027"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengmin Xu","raw_affiliation_strings":["School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104128998","display_name":"Gang Wu","orcid":"https://orcid.org/0009-0003-9953-3543"},"institutions":[{"id":"https://openalex.org/I3129293551","display_name":"Tarim University","ror":"https://ror.org/05202v862","country_code":"CN","type":"education","lineage":["https://openalex.org/I3129293551"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wu","raw_affiliation_strings":["College of Cyber Security, Tarim University, Tarim, Xinjiang, China"],"affiliations":[{"raw_affiliation_string":"College of Cyber Security, Tarim University, Tarim, Xinjiang, China","institution_ids":["https://openalex.org/I3129293551"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100741750","display_name":"Zhongyuan Wang","orcid":"https://orcid.org/0000-0002-9796-488X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyuan Wang","raw_affiliation_strings":["National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I174442536"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37015572,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9976000189781189,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.0003000000142492354,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8119000196456909},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6536999940872192},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.6294999718666077},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5424000024795532},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5095000267028809},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5094000101089478},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5090000033378601},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.385699987411499}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8119000196456909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7477999925613403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6970000267028809},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6536999940872192},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6294999718666077},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5095000267028809},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5094000101089478},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5090000033378601},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.385699987411499},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37400001287460327},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3743093.3771076","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3743093.3771076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Multimedia in Asia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5579350893","display_name":null,"funder_award_id":"62371350, 62372339","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":35,"referenced_works":["https://openalex.org/W2093935825","https://openalex.org/W2322772590","https://openalex.org/W2510190030","https://openalex.org/W2548928501","https://openalex.org/W2788751553","https://openalex.org/W2791820053","https://openalex.org/W2883429621","https://openalex.org/W2960957522","https://openalex.org/W2963820951","https://openalex.org/W2963854019","https://openalex.org/W2966138416","https://openalex.org/W2977530922","https://openalex.org/W2988630963","https://openalex.org/W3014370958","https://openalex.org/W3035400973","https://openalex.org/W3046961188","https://openalex.org/W3093108399","https://openalex.org/W3097009184","https://openalex.org/W3127230993","https://openalex.org/W3180933213","https://openalex.org/W3195852174","https://openalex.org/W3201864842","https://openalex.org/W3202075110","https://openalex.org/W3203640349","https://openalex.org/W4206065772","https://openalex.org/W4285219686","https://openalex.org/W4312652114","https://openalex.org/W4313190226","https://openalex.org/W4313447175","https://openalex.org/W4386038376","https://openalex.org/W4386065354","https://openalex.org/W4386071489","https://openalex.org/W4390872967","https://openalex.org/W4390872985","https://openalex.org/W4408803960"],"related_works":[],"abstract_inverted_index":{"Gait":[0],"recognition":[1,157],"has":[2],"become":[3],"an":[4],"increasingly":[5],"important":[6],"biometric":[7],"technique":[8],"for":[9,34],"identifying":[10],"individuals":[11],"from":[12],"a":[13,23,48,69,96,125],"distance":[14],"without":[15],"requiring":[16],"their":[17],"active":[18],"cooperation.":[19],"Since":[20],"gait":[21,90,156],"involves":[22],"sequence":[24],"of":[25,59],"motion":[26,60,143],"patterns,":[27],"effectively":[28],"capturing":[29,141],"temporal":[30,41,87,138,147],"dynamics":[31],"is":[32],"essential":[33],"accurate":[35],"recognition.":[36],"Traditional":[37],"methods":[38],"that":[39,101,167],"extract":[40],"features":[42],"independently":[43],"and":[44,57,86,107,117,162,190],"fuse":[45],"them":[46],"at":[47],"later":[49],"stage":[50],"often":[51],"fail":[52],"to":[53,113,131,136,175],"model":[54,137],"the":[55,104,111,133],"continuity":[56],"interdependence":[58],"across":[61,145],"frames.":[62],"To":[63],"overcome":[64],"this":[65],"limitation,":[66],"we":[67,123],"propose":[68],"novel":[70],"three-dimensional":[71],"convolutional":[72,99],"architecture":[73,94],"named":[74],"Robust":[75],"Spatiotemporal":[76],"3D":[77,98,177],"Convolutional":[78],"Neural":[79],"Network":[80],"(RST3D),":[81],"which":[82],"jointly":[83],"captures":[84],"spatial":[85],"correlations":[88],"throughout":[89],"sequences.":[91],"The":[92],"proposed":[93],"incorporates":[95],"comprehensive":[97],"block":[100,130],"operates":[102],"along":[103],"temporal,":[105],"height,":[106],"width":[108],"dimensions,":[109],"enabling":[110],"network":[112],"learn":[114],"more":[115],"expressive":[116],"coherent":[118],"spatiotemporal":[119],"representations.":[120],"In":[121],"addition,":[122],"introduce":[124],"Temporal":[126],"Pyramidal":[127],"Attention":[128],"(TPA)":[129],"enhance":[132],"network\u2019s":[134],"ability":[135],"dependencies":[139],"by":[140],"discriminative":[142],"patterns":[144],"multiple":[146],"scales.":[148],"We":[149],"evaluate":[150],"our":[151,168],"method":[152],"on":[153],"four":[154],"large-scale":[155],"datasets:":[158],"CASIA-B,":[159],"OUMVLP,":[160],"GREW,":[161],"Gait3D.":[163],"Experimental":[164],"results":[165],"show":[166],"approach":[169],"consistently":[170],"achieves":[171],"superior":[172],"performance":[173],"compared":[174],"existing":[176],"CNN-based":[178],"methods,":[179],"particularly":[180],"under":[181],"challenging":[182],"conditions":[183],"such":[184],"as":[185],"view":[186],"variation,":[187],"clothing":[188],"changes,":[189],"occlusion.":[191]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-12-06T00:00:00"}