{"id":"https://openalex.org/W7164821817","doi":"https://doi.org/10.1145/3805622.3810579","title":"LTA-Gait: In-Network Temporal Activation of Large Vision Models for Gait Recognition","display_name":"LTA-Gait: In-Network Temporal Activation of Large Vision Models for Gait Recognition","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164821817","doi":"https://doi.org/10.1145/3805622.3810579"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810579","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810579","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810579","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138667841","display_name":"Qichao Zhang","orcid":"https://orcid.org/0009-0006-7012-0480"},"institutions":[{"id":"https://openalex.org/I107982497","display_name":"Dalian Ocean University","ror":"https://ror.org/0523b6g79","country_code":"CN","type":"education","lineage":["https://openalex.org/I107982497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qichao Zhang","raw_affiliation_strings":["Dalian Ocean University, Dalian, China"],"raw_orcid":"https://orcid.org/0009-0006-7012-0480","affiliations":[{"raw_affiliation_string":"Dalian Ocean University, Dalian, China","institution_ids":["https://openalex.org/I107982497"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103253915","display_name":"Genlang Chen","orcid":"https://orcid.org/0000-0003-4381-7988"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genlang Chen","raw_affiliation_strings":["NingboTech University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0003-4381-7988","affiliations":[{"raw_affiliation_string":"NingboTech University, Ningbo, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028910864","display_name":"Chengcheng Jia","orcid":"https://orcid.org/0000-0002-9562-5278"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengcheng Jia","raw_affiliation_strings":["NingboTech University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0002-9562-5278","affiliations":[{"raw_affiliation_string":"NingboTech University, Ningbo, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089401815","display_name":"Jiajian Zhang","orcid":"https://orcid.org/0000-0003-2903-9411"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajian Zhang","raw_affiliation_strings":["NingboTech University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0003-2903-9411","affiliations":[{"raw_affiliation_string":"NingboTech University, Ningbo, China","institution_ids":["https://openalex.org/I159389169"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.87576473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1166","last_page":"1173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9829999804496765,"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":0.9829999804496765,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.004000000189989805,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.0031999999191612005,"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/granularity","display_name":"Granularity","score":0.47200000286102295},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4390999972820282},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38960000872612},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.38429999351501465},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.3822000026702881},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.37790000438690186},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.37540000677108765},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.37059998512268066},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.36390000581741333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7653999924659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5961999893188477},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.47200000286102295},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4575999975204468},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4390999972820282},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.3822000026702881},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.37540000677108765},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.35740000009536743},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.30640000104904175},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.2621999979019165},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810579","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810579","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810579","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810579","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2963301258","https://openalex.org/W3035400973","https://openalex.org/W4379652859","https://openalex.org/W4386065354","https://openalex.org/W4386071649","https://openalex.org/W4393154968","https://openalex.org/W4393159850","https://openalex.org/W4402660067","https://openalex.org/W4404238782","https://openalex.org/W4409262549","https://openalex.org/W4409368693","https://openalex.org/W4413147802","https://openalex.org/W7133219196","https://openalex.org/W7133241830"],"related_works":[],"abstract_inverted_index":{"While":[0],"gait":[1,99,202],"recognition":[2],"based":[3],"on":[4,175],"Large":[5],"Vision":[6],"Models":[7,62],"(LVMs)":[8],"benefits":[9],"from":[10],"powerful":[11],"spatial":[12,161],"representations,":[13],"existing":[14],"paradigms":[15],"often":[16],"reduce":[17],"video":[18,41],"sequences":[19],"to":[20,98,122,137,152],"unordered":[21],"image":[22,37],"sets,":[23],"inherently":[24],"neglecting":[25],"the":[26,32,45,52,56,67,87,135,159,164,192],"inter-frame":[27],"temporal":[28,72,80,127,148,155],"causality.":[29],"To":[30],"bridge":[31],"modal":[33],"gap":[34],"between":[35],"static":[36],"perception":[38],"and":[39,51,93,181],"dynamic":[40],"understanding,":[42],"we":[43,101,115,144],"propose":[44],"Layer-wise":[46],"Spatio-Temporal":[47],"Activation":[48],"(LTA)":[49],"framework":[50],"LTA-Gait":[53,170],"model.":[54],"Leveraging":[55],"linear":[57],"complexity":[58],"of":[59,70,89,163,195],"State":[60],"Space":[61],"(SSMs),":[63],"our":[64,211],"method":[65],"alleviates":[66],"efficiency":[68],"challenge":[69],"introducing":[71,109],"modeling":[73,156,198],"into":[74],"deep":[75],"LVMs,":[76],"enabling":[77],"full-level":[78],"dense":[79],"adaptation":[81],"in":[82,187,199],"a":[83,117,146],"practical":[84],"manner.":[85],"Addressing":[86],"challenges":[88],"recursive":[90],"noise":[91,125],"sensitivity":[92],"spatio-temporal":[94],"granularity":[95,157],"misalignment":[96],"specific":[97],"video,":[100],"design":[102],"an":[103,110],"Anatomy-Aware":[104],"Temporal":[105],"Adapter":[106],"(AATA).":[107],"By":[108],"input-output":[111],"synergistic":[112],"dual-gating":[113],"mechanism,":[114],"apply":[116],"binary":[118],"mask-based":[119],"input":[120],"constraint":[121],"suppress":[123],"background":[124],"before":[126],"recursion,":[128],"while":[129],"using":[130],"adaptive":[131],"soft":[132],"gating":[133],"at":[134,210],"output":[136],"stabilize":[138],"feature":[139],"injection":[140],"during":[141],"fine-tuning.":[142],"Furthermore,":[143],"construct":[145],"progressive":[147],"receptive":[149],"field":[150],"strategy":[151],"better":[153],"match":[154],"with":[158],"hierarchical":[160],"features":[162],"LVM.":[165],"Extensive":[166],"experiments":[167],"demonstrate":[168],"that":[169],"achieves":[171],"State-of-the-Art":[172],"(SOTA)":[173],"performance":[174,185],"benchmarks":[176],"such":[177],"as":[178],"CCPG,":[179],"CCGR,":[180],"CASIA-B*.":[182],"Notably,":[183],"significant":[184],"gains":[186],"challenging":[188],"clothing-change":[189],"scenarios":[190],"validate":[191],"core":[193],"value":[194],"robust":[196],"ordered":[197],"extracting":[200],"intrinsic":[201],"dynamics.":[203],"All":[204],"implementation":[205],"code":[206],"is":[207],"fully":[208],"available":[209],"project":[212],"repository:":[213],"https://github.com/zjucgl/LTA-Gait.":[214]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}