MCDGait: Multimodal Co-Learning Distillation Network with Spatial-Temporal Graph Reasoning for Gait Recognition in the Wild

MCDGait: Multimodal Co-Learning Distillation Network with Spatial-Temporal Graph Reasoning for Gait Recognition in the Wild | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article MCDGait: Multimodal Co-Learning Distillation Network with Spatial-Temporal Graph Reasoning for Gait Recognition in the Wild Jianbo Xiong, Shinan Zou, Jin Tang, Tjahjadi Tardi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4037908/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jun, 2024 Read the published version in The Visual Computer → Version 1 posted 9 You are reading this latest preprint version Abstract Gait recognition in the wild has attracted the attention of the academic community. However, existing unimodal algorithms cannot achieve the same performance on in-the-wild datasets as in-the-lab datasets because unimodal data have many limitations in-the-wild environments. Therefore, we propose a multimodal approach combining silhouettes and skeletons and formulates the multimodal gait recognition problem as a multimodal co-learning problem. In particular, we propose a multimodal co-learning distillation network (MCDGait) that integrates two student networks processing unimodal data into a single teacher network. Based on the semantic consistency of different modalities and the paradigm of deep mutual learning, the performance of the entire network is continuously improved via the bidirectional knowledge distillation between the student and teacher networks. Inspired by the observation that specific body parts or joints exhibit unique motion characteristics and have linkage with other parts or joints during walking, we propose a spatial-temporal graph reasoning module (ST-GRM). This module represents the parts or joints as graph nodes and the motion linkages between them as edges. By utilizing dynamic graph generator, the module implicitly captures the dynamic changes of the human body. Based on the generated graphs, the independent spatial-temporal linkage feature of each part and the interactive spatial-temporal linkage feature are aggregated simultaneously. Extensive experiments conducted on two in-the-wild datasets demonstrate the state-of-the-art performance of the proposed method. The average rank-1 accuracy on datasets Gait3D and GREW is 50.90% and 58.06%, respectively. The source code can be obtained from https://github.com/BoyeXiong/MCDGait . Biometrics Human identification Gait recognition Multimodal Co-Learning Distillation Spatial-Temporal Graph Reasoning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Jun, 2024 Read the published version in The Visual Computer → Version 1 posted Editorial decision: Revision requested 29 Mar, 2024 Reviews received at journal 21 Mar, 2024 Reviews received at journal 18 Mar, 2024 Reviewers agreed at journal 14 Mar, 2024 Reviewers agreed at journal 12 Mar, 2024 Reviewers invited by journal 12 Mar, 2024 Editor assigned by journal 10 Mar, 2024 Submission checks completed at journal 10 Mar, 2024 First submitted to journal 08 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4037908","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278866576,"identity":"3909693f-5b40-4060-ad1b-9472c3127a97","order_by":0,"name":"Jianbo Xiong","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Jianbo","middleName":"","lastName":"Xiong","suffix":""},{"id":278866577,"identity":"8764bcfc-3b3a-46fd-b730-c753a07bba29","order_by":1,"name":"Shinan Zou","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Shinan","middleName":"","lastName":"Zou","suffix":""},{"id":278866578,"identity":"048dd413-51d1-4321-ad2b-5d610afd548c","order_by":2,"name":"Jin Tang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYFCCgw0MHyAsA+I08AC1MM4gUQsDAzMPSVrsGQ+3PbapqUtsYG/eJsFQc4coh7Ub5xw7nNjAc6xMguHYM6K0tEnnNhxIbJDIMZNgbDhMpBbLBqDD5N+QooWxgRloCw+xWg4cbJPsOXbYuI0nrdgi4RgRWthnHH8m8aOmTraf/fDGGx9qiNDCIHEAQrOBiAQiNDAw8DcQpWwUjIJRMApGMgAAizY3bs3uqskAAAAASUVORK5CYII=","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Jin","middleName":"","lastName":"Tang","suffix":""},{"id":278866579,"identity":"664458f2-b527-4592-a222-10d2dec0befa","order_by":3,"name":"Tjahjadi Tardi","email":"","orcid":"","institution":"University of Warwick","correspondingAuthor":false,"prefix":"","firstName":"Tjahjadi","middleName":"","lastName":"Tardi","suffix":""}],"badges":[],"createdAt":"2024-03-08 06:37:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4037908/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4037908/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00371-024-03426-y","type":"published","date":"2024-06-15T15:38:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58823468,"identity":"762cc842-4e50-47bd-bb25-42c175368374","added_by":"auto","created_at":"2024-06-21 16:59:52","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1025947,"visible":true,"origin":"","legend":"","description":"","filename":"snarticletemplate.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4037908/v1_covered_fc3a7f05-00d4-4026-979d-e3443c72dadc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"MCDGait: Multimodal Co-Learning Distillation Network with Spatial-Temporal Graph Reasoning for Gait Recognition in the Wild","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-visual-computer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tvcj","sideBox":"Learn more about [The Visual Computer](http://link.springer.com/journal/371)","snPcode":"371","submissionUrl":"https://submission.nature.com/new-submission/371/3","title":"The Visual Computer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Biometrics, Human identification, Gait recognition, Multimodal Co-Learning Distillation, Spatial-Temporal Graph Reasoning","lastPublishedDoi":"10.21203/rs.3.rs-4037908/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4037908/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Gait recognition in the wild has attracted the attention of the academic community. 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