{"id":"https://openalex.org/W7138847357","doi":"https://doi.org/10.1109/tifs.2026.3675459","title":"Language as a Bridge: Semantic-Guided Cross-Modal Gait Recognition via Text Prototype and Feature Decoupling","display_name":"Language as a Bridge: Semantic-Guided Cross-Modal Gait Recognition via Text Prototype and Feature Decoupling","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7138847357","doi":"https://doi.org/10.1109/tifs.2026.3675459"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2026.3675459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3675459","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-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/A5002183372","display_name":"Zhiyang Lu","orcid":"https://orcid.org/0009-0000-8161-428X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyang Lu","raw_affiliation_strings":["Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505","https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070577436","display_name":"Wankang Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wankang Zeng","raw_affiliation_strings":["Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505","https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130079697","display_name":"Ming Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Cheng","raw_affiliation_strings":["Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505","https://openalex.org/I75867142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129795517","display_name":"Cheng Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Urban Intelligent Sensing and Computing, Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505","https://openalex.org/I75867142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002183372"],"corresponding_institution_ids":["https://openalex.org/I191208505","https://openalex.org/I75867142"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82214662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"3038","last_page":"3052"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9904999732971191,"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":0.9904999732971191,"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":0.0015999999595806003,"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":0.0010000000474974513,"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/gait","display_name":"Gait","score":0.6430000066757202},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5231999754905701},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.43389999866485596},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4332999885082245},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.41780000925064087},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.41339999437332153},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.40779998898506165},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.39570000767707825},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.38359999656677246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8474000096321106},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6430000066757202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5633999705314636},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5231999754905701},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.41339999437332153},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.39570000767707825},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3635999858379364},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.328900009393692},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.31189998984336853},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2939000129699707}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2026.3675459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3675459","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5416120290756226,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1546677826","https://openalex.org/W1563917320","https://openalex.org/W2016327746","https://openalex.org/W2102742858","https://openalex.org/W2104335344","https://openalex.org/W2117281018","https://openalex.org/W2126680226","https://openalex.org/W2135541996","https://openalex.org/W2194775991","https://openalex.org/W2739353222","https://openalex.org/W2788751553","https://openalex.org/W2960957522","https://openalex.org/W2963301258","https://openalex.org/W2963854019","https://openalex.org/W2982294548","https://openalex.org/W3035400973","https://openalex.org/W3046961188","https://openalex.org/W3128064349","https://openalex.org/W3129630843","https://openalex.org/W3198377975","https://openalex.org/W3201864842","https://openalex.org/W3204075450","https://openalex.org/W4312480274","https://openalex.org/W4312652114","https://openalex.org/W4364302332","https://openalex.org/W4382999123","https://openalex.org/W4386065354","https://openalex.org/W4386065639","https://openalex.org/W4386071994","https://openalex.org/W4386076037","https://openalex.org/W4386523789","https://openalex.org/W4387010831","https://openalex.org/W4387789881","https://openalex.org/W4388263168","https://openalex.org/W4390872891","https://openalex.org/W4390874481","https://openalex.org/W4391093084","https://openalex.org/W4392426151","https://openalex.org/W4399310645","https://openalex.org/W4400648131","https://openalex.org/W4402753283","https://openalex.org/W4402753418","https://openalex.org/W4402754304","https://openalex.org/W4403758820","https://openalex.org/W4403791505","https://openalex.org/W4403888955","https://openalex.org/W4404238758","https://openalex.org/W4408017547","https://openalex.org/W4409367328","https://openalex.org/W4410986256","https://openalex.org/W4413555875","https://openalex.org/W4415795625","https://openalex.org/W7083290702","https://openalex.org/W7133196460"],"related_works":[],"abstract_inverted_index":{"Gait":[0,90,111,185],"recognition":[1,91],"aims":[2],"to":[3,73,78,102,148,173,223],"identify":[4],"individuals":[5],"based":[6],"on":[7],"walking":[8],"patterns":[9],"in":[10,208],"a":[11,30,56,87],"long-range,":[12],"contactless":[13],"manner.":[14],"While":[15],"camera-based":[16],"methods":[17],"have":[18],"advanced":[19],"significantly,":[20],"their":[21],"performance":[22],"deteriorates":[23],"under":[24],"poor":[25],"lighting":[26],"conditions.":[27],"LiDAR":[28,52,106],"offers":[29],"promising":[31],"alternative":[32],"by":[33,215],"capturing":[34],"accurate":[35],"3D":[36],"gait":[37,61,231],"information":[38],"regardless":[39],"of":[40,198,230],"illumination.":[41],"However,":[42],"effectively":[43],"integrating":[44],"heterogeneous":[45],"data":[46],"from":[47,145],"diverse":[48],"sensors,":[49],"such":[50],"as":[51,98],"and":[53,76,105,115,126,137,166,176,233,237],"cameras,":[54],"remains":[55],"key":[57],"challenge":[58],"for":[59,122,162],"cross-modal":[60],"recognition.":[62],"Existing":[63],"approaches":[64],"often":[65],"minimize":[66],"modality":[67],"discrepancy":[68],"directly,":[69],"which":[70],"can":[71],"lead":[72],"class":[74],"collapse":[75],"damage":[77],"inter-class":[79],"discriminability.":[80],"To":[81],"overcome":[82],"these":[83],"limitations,":[84],"we":[85],"propose":[86,155],"Semantic-Guided":[88,168],"Cross-modal":[89],"framework,":[92],"SG-CrossGait,":[93],"that":[94],"introduces":[95],"text":[96,127,150],"features":[97],"the":[99,149,156,167,196,212,220,228],"prototype":[100,151],"space":[101],"bridge":[103],"camera":[104],"modalities.":[107],"We":[108,153,217],"design":[109],"structured":[110],"Description":[112],"Factors":[113],"(GDF)":[114],"leverage":[116],"multimodal":[117],"large":[118],"language":[119],"models":[120],"(MLLMs)":[121],"automatic":[123],"factor":[124],"annotation":[125],"generation,":[128],"enriching":[129],"existing":[130],"datasets":[131,238],"with":[132],"textual":[133],"descriptions,":[134],"yielding":[135],"SUSTech1K-Text":[136],"FreeGait-Text.":[138],"A":[139,179],"CLIP-based":[140],"pipeline":[141],"aligns":[142],"multi-grained":[143],"representations":[144],"both":[146],"modalities":[147],"space.":[152],"further":[154,189],"Dual-stream":[157],"Cross-attention":[158],"Fusion":[159],"(DCF)":[160],"module":[161,172],"fine-grained":[163],"feature":[164],"integration":[165],"Feature":[169],"Decoupling":[170],"(SGFD)":[171],"disentangle":[174],"shared":[175],"modality-specific":[177],"features.":[178],"Multi-task":[180],"Training":[181],"(MT)":[182],"scheme":[183],"incorporating":[184],"Attribute":[186],"Recognition":[187],"(GAR)":[188],"enhances":[190],"intra-class":[191],"compactness.":[192],"Extensive":[193],"experiments":[194],"validate":[195],"effectiveness":[197],"our":[199,203],"approach.":[200],"On":[201],"SUSTech1K-Text,":[202],"method":[204,214],"achieves":[205],"61%":[206],"accuracy":[207],"LiDAR-to-Camera":[209],"recognition,":[210],"outperforming":[211],"state-of-the-art":[213],"8.3%.":[216],"also":[218],"release":[219],"Gait-Text":[221],"benchmark":[222],"promote":[224],"future":[225],"research":[226],"at":[227],"intersection":[229],"analysis":[232],"vision-language":[234],"learning.":[235],"Code":[236],"are":[239],"available":[240],"at:":[241],"https://github.com/O-VIGIA/SCCG.git.":[242]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2026-03-20T00:00:00"}
