{"id":"https://openalex.org/W7133336507","doi":"https://doi.org/10.1109/ijcb65343.2025.11410992","title":"Learning Dynamic Gait Regions: Adaptive Part Weighting UDA for Cross-domain Gait Recognition","display_name":"Learning Dynamic Gait Regions: Adaptive Part Weighting UDA for Cross-domain Gait Recognition","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W7133336507","doi":"https://doi.org/10.1109/ijcb65343.2025.11410992"},"language":null,"primary_location":{"id":"doi:10.1109/ijcb65343.2025.11410992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11410992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","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/A5127972360","display_name":"Yicheng Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicheng Cao","raw_affiliation_strings":["Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124920105","display_name":"Hanqi Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqi Lyu","raw_affiliation_strings":["Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127969432","display_name":"Min Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5127906466","display_name":"Yan Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Sun","raw_affiliation_strings":["Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54614628,"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":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9896000027656555,"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":0.9896000027656555,"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":0.003800000064074993,"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/T10860","display_name":"Speech and Audio Processing","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.7465000152587891},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.697700023651123},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.6276999711990356},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5030999779701233},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.49470001459121704},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.4797999858856201},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4620000123977661},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41819998621940613},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.41200000047683716}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7465000152587891},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7319999933242798},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.697700023651123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452999711036682},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6276999711990356},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5030999779701233},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.49470001459121704},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4620000123977661},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41670000553131104},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3882000148296356},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35350000858306885},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.3142000138759613},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb65343.2025.11410992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11410992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2026800967","https://openalex.org/W2058897916","https://openalex.org/W2104335344","https://openalex.org/W2126680226","https://openalex.org/W2154624311","https://openalex.org/W2322772590","https://openalex.org/W2739325416","https://openalex.org/W2745659361","https://openalex.org/W2953214814","https://openalex.org/W2963000559","https://openalex.org/W2963301258","https://openalex.org/W2977530922","https://openalex.org/W2988852559","https://openalex.org/W3009761962","https://openalex.org/W3035070480","https://openalex.org/W3109072956","https://openalex.org/W3134385809","https://openalex.org/W3158409426","https://openalex.org/W3203755984","https://openalex.org/W4292198371","https://openalex.org/W4310494058","https://openalex.org/W4312652114","https://openalex.org/W4313013512","https://openalex.org/W4386065354","https://openalex.org/W4386076037","https://openalex.org/W4386472834","https://openalex.org/W4390872985","https://openalex.org/W4394597484","https://openalex.org/W4408017547"],"related_works":[],"abstract_inverted_index":{"Gait":[0],"recognition":[1],"has":[2],"emerged":[3],"as":[4,70],"a":[5,86,121,148],"promising":[6],"biometric":[7],"identification":[8],"technology":[9],"due":[10],"to":[11,37,39,65,76,139],"its":[12,20],"non-invasive":[13],"nature":[14],"and":[15,54,74,112,129,143,160],"long-distance":[16],"capture":[17],"capabilities.":[18],"However,":[19],"practical":[21],"deployment":[22],"faces":[23],"challenges":[24,93],"in":[25,49,94,189],"cross-domain":[26,95,190],"scenarios,":[27],"where":[28],"models":[29],"trained":[30],"on":[31,134,181],"labeled":[32],"source":[33],"domain":[34],"data":[35],"struggle":[36],"generalize":[38],"unlabeled":[40],"target":[41],"domains":[42],"with":[43],"divergent":[44],"distributions":[45],"caused":[46],"by":[47,166],"variations":[48],"illumination,":[50],"clothing,":[51],"camera":[52],"angles,":[53],"environmental":[55],"factors.":[56],"Existing":[57],"Unsupervised":[58],"Domain":[59],"Adaptation":[60],"(UDA)":[61],"techniques":[62],"often":[63],"fail":[64],"address":[66],"key":[67],"issues":[68],"such":[69],"hard":[71],"sample":[72,169],"mining":[73],"robustness":[75,162],"dynamic":[77],"gait":[78,96,153],"features.":[79],"In":[80],"this":[81],"work,":[82],"we":[83],"propose":[84],"DyUDA,":[85],"novel":[87],"framework":[88,177],"that":[89,174],"effectively":[90],"addresses":[91],"these":[92],"recognition.":[97],"First,":[98],"an":[99],"Adaptive":[100],"Part":[101],"Weighting":[102],"(APW)":[103],"module":[104],"dynamically":[105],"prioritizes":[106],"motion-relevant":[107],"body":[108],"regions":[109],"(e.g.,":[110],"head":[111],"feet),":[113],"reducing":[114],"the":[115],"impact":[116],"of":[117],"appearance":[118],"variation.":[119],"Second,":[120],"Mix-sim":[122],"Sampler":[123],"categorizes":[124],"samples":[125],"into":[126,155],"high-similarity":[127],"(high-sim)":[128],"low-similarity":[130],"(low-sim)":[131],"groups":[132],"based":[133],"cosine":[135],"similarity,":[136],"leveraging":[137],"both":[138],"optimize":[140],"pseudo-label":[141],"quality":[142],"mitigate":[144],"training":[145],"instability.":[146],"Third,":[147],"Temporal":[149],"Segmentation":[150],"approach":[151],"splits":[152],"sequences":[154],"sub-segments,":[156],"enriching":[157],"feature":[158],"diversity":[159],"improving":[161],"against":[163],"viewpoint":[164],"changes":[165],"expanding":[167],"positive":[168],"pairs.":[170],"Extensive":[171],"experiments":[172],"demonstrate":[173],"our":[175],"DyUDA":[176],"achieves":[178],"state-of-the-art":[179],"performance":[180],"benchmark":[182],"datasets,":[183],"significantly":[184],"outperforming":[185],"existing":[186],"UDA":[187],"methods":[188],"accuracy":[191],"while":[192],"maintaining":[193],"stability":[194],"under":[195],"complex":[196],"real-world":[197],"conditions.":[198]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-03-04T00:00:00"}
