{"id":"https://openalex.org/W4403791741","doi":"https://doi.org/10.1145/3664647.3680812","title":"GLGait: A Global-Local Temporal Receptive Field Network for Gait Recognition in the Wild","display_name":"GLGait: A Global-Local Temporal Receptive Field Network for Gait Recognition in the Wild","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791741","doi":"https://doi.org/10.1145/3664647.3680812"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3680812","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5063073212","display_name":"Guozhen Peng","orcid":"https://orcid.org/0009-0005-7386-6475"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guozhen Peng","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-7386-6475","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398953","display_name":"Yunhong Wang","orcid":"https://orcid.org/0000-0001-8001-2703"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhong Wang","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8001-2703","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100300967","display_name":"Yuwei Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Zhao","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-1537-0715","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062716361","display_name":"Shaoxiong Zhang","orcid":"https://orcid.org/0000-0003-2772-8336"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoxiong Zhang","raw_affiliation_strings":["The School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0003-2772-8336","affiliations":[{"raw_affiliation_string":"The School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012121355","display_name":"Annan Li","orcid":"https://orcid.org/0000-0003-3497-5052"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Annan Li","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3497-5052","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5063073212"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":1.2197,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77631151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"826","last_page":"835"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":1.0,"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":1.0,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9961000084877014,"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/gait","display_name":"Gait","score":0.6995010375976562},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.6813606023788452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6033029556274414},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5694654583930969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49297118186950684},{"id":"https://openalex.org/keywords/gait-analysis","display_name":"Gait analysis","score":0.4384008049964905},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3778870105743408},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3712029457092285},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32477641105651855},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.3000921905040741},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1061905026435852},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08962658047676086}],"concepts":[{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6995010375976562},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.6813606023788452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6033029556274414},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5694654583930969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49297118186950684},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.4384008049964905},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3778870105743408},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3712029457092285},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32477641105651855},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.3000921905040741},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1061905026435852},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08962658047676086},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3680812","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W2112796928","https://openalex.org/W2151458682","https://openalex.org/W2520774990","https://openalex.org/W2612690371","https://openalex.org/W2788751553","https://openalex.org/W2789834341","https://openalex.org/W2963301258","https://openalex.org/W2963744743","https://openalex.org/W2963820951","https://openalex.org/W2977530922","https://openalex.org/W3042230461","https://openalex.org/W3092754310","https://openalex.org/W3097009184","https://openalex.org/W3106350522","https://openalex.org/W3138516171","https://openalex.org/W3182137715","https://openalex.org/W3195852174","https://openalex.org/W3201864842","https://openalex.org/W4212774754","https://openalex.org/W4214538268","https://openalex.org/W4214612132","https://openalex.org/W4225145979","https://openalex.org/W4285130367","https://openalex.org/W4292793985","https://openalex.org/W4312560592","https://openalex.org/W4312623054","https://openalex.org/W4312652114","https://openalex.org/W4360994141","https://openalex.org/W4375868842","https://openalex.org/W4385572928","https://openalex.org/W4386076037","https://openalex.org/W4386076281","https://openalex.org/W4386523789","https://openalex.org/W4387789881","https://openalex.org/W4387968226","https://openalex.org/W4390874575"],"related_works":["https://openalex.org/W2133973503","https://openalex.org/W2471060339","https://openalex.org/W2148547327","https://openalex.org/W1989734657","https://openalex.org/W4226236273","https://openalex.org/W2125892956","https://openalex.org/W4226004263","https://openalex.org/W2130975749","https://openalex.org/W2493973380","https://openalex.org/W2394835211"],"abstract_inverted_index":{"Gait":[0],"recognition":[1,13,59],"has":[2],"attracted":[3],"increasing":[4],"attention":[5],"from":[6,15],"academia":[7],"and":[8,143,163,218,241],"industry":[9],"as":[10],"a":[11,16,92,102,112,121,128,137,144,154,168,196,206],"human":[12],"technology":[14],"distance":[17,217],"in":[18,31,39,60,211,223],"non-intrusive":[19],"ways":[20],"without":[21],"requiring":[22],"cooperation.":[23],"Although":[24],"advanced":[25],"methods":[26,49],"have":[27,50],"achieved":[28],"impressive":[29],"success":[30],"lab":[32],"scenarios,":[33],"most":[34],"of":[35,57,136],"them":[36],"perform":[37],"poorly":[38],"the":[40,55,61,64,87,180,215,220,224],"wild.":[41,62],"Recently,":[42],"some":[43],"Convolution":[44],"Neural":[45],"Networks":[46],"(ConvNets)":[47],"based":[48],"been":[51],"proposed":[52],"to":[53,126,152,178,195,213],"address":[54,107],"issue":[56],"gait":[58,76,104],"However,":[63],"temporal":[65,94,130,145,157,173,182,192,199],"receptive":[66,95,131,158,183,193,200],"field":[67,159,194],"obtained":[68],"by":[69],"convolution":[70,81,146,174],"operations":[71],"is":[72,98,150,176,245],"limited":[73],"for":[74,100],"long":[75],"sequences.":[77],"If":[78],"directly":[79],"replacing":[80],"blocks":[82],"with":[83,160,167],"visual":[84],"transformer":[85],"blocks,":[86],"model":[88],"may":[89],"not":[90],"enhance":[91,179],"local":[93,181],"field,":[96,132],"which":[97,133],"important":[99],"covering":[101],"complete":[103],"cycle.":[105],"To":[106],"this":[108],"issue,":[109],"we":[110,203],"design":[111],"Global-Local":[113,122],"Temporal":[114,123,140],"Receptive":[115],"Field":[116],"Network":[117],"(GLGait).":[118],"GLGait":[119,212],"employs":[120],"Module":[124],"(GLTM)":[125],"establish":[127],"global-local":[129],"mainly":[134],"consists":[135],"Pseudo":[138],"Global":[139],"Self-Attention":[141],"(PGTA)":[142],"operation.":[147],"Specifically,":[148],"PGTA":[149],"used":[151,177],"obtain":[153],"pseudo":[155,190],"global":[156,191],"less":[161],"memory":[162],"computation":[164],"complexity":[165],"compared":[166],"multi-head":[169],"self-attention":[170],"(MHSA).":[171],"The":[172,243],"operation":[175],"field.":[184,201],"Besides,":[185],"it":[186],"can":[187],"also":[188,204],"aggregate":[189],"true":[197],"holistic":[198],"Furthermore,":[202],"propose":[205],"Center-Augmented":[207],"Triplet":[208],"Loss":[209],"(CTL)":[210],"reduce":[214],"intra-class":[216],"expand":[219],"positive":[221],"samples":[222],"training":[225],"stage.":[226],"Extensive":[227],"experiments":[228],"show":[229],"that":[230],"our":[231],"method":[232],"obtains":[233],"state-of-the-art":[234],"results":[235],"on":[236],"in-the-wild":[237],"datasets,":[238],"i.e.,":[239],"Gait3D":[240],"GREW.":[242],"code":[244],"available":[246],"at":[247],"https://github.com/bgdpgz/GLGait.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}