{"paper_id":"3fc22be3-64bf-4d51-91b8-d617b80b01f7","body_text":"DiffFish: A Unified Diffusion Model for Robust Multi-Object Fish Tracking in Aquaculture | 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 DiffFish: A Unified Diffusion Model for Robust Multi-Object Fish Tracking in Aquaculture Kexin Yuan, Yunchen Tian, Jianing Quan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8485463/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Apr, 2026 Read the published version in The Visual Computer → Version 1 posted 10 You are reading this latest preprint version Abstract In aquaculture, precise monitoring of fish behavior is crucial for breeding superior strains. Traditional tracking methods face challenges such as occlusion, deformation, and complex underwater environments. To address these, we propose DiffFish, a diffusion model-based framework that unifies object detection and association for multi-object fish tracking. DiffFish employs dynamic fish mask insertion and a random frame-skipping strategy to enhance robustness and reduce trajectory fragmentation. Experimental results on the LC-MOT dataset demonstrate DiffFish's superior performance with 93.9% MOTA and 75.6% IDF1, outperforming existing methods. This approach provides an efficient solution for analyzing fish motion and behavior in aquaculture. The dataset and codes are publicly available at https://github.com/arya7bling-blip/DiffFish . Multi-object fish tracking Diffusion model Frame-skipping Learning Dynamic object insertion Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 27 Apr, 2026 Read the published version in The Visual Computer → Version 1 posted Editorial decision: Revision requested 16 Feb, 2026 Reviews received at journal 15 Feb, 2026 Reviewers agreed at journal 14 Feb, 2026 Reviews received at journal 05 Feb, 2026 Reviewers agreed at journal 30 Jan, 2026 Reviewers agreed at journal 29 Jan, 2026 Reviewers invited by journal 28 Jan, 2026 Editor assigned by journal 31 Dec, 2025 Submission checks completed at journal 31 Dec, 2025 First submitted to journal 30 Dec, 2025 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-8485463\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":587612358,\"identity\":\"14371d4c-2c95-40b2-b1aa-c1b93ee5553c\",\"order_by\":0,\"name\":\"Kexin Yuan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Tianjin Agricultural University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kexin\",\"middleName\":\"\",\"lastName\":\"Yuan\",\"suffix\":\"\"},{\"id\":587612359,\"identity\":\"49f17b5e-2675-4c81-8117-113190bb8173\",\"order_by\":1,\"name\":\"Yunchen Tian\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYDACZihtwMDA+ICBB8bGA3iQtDAbHCBKC4wBVMYmcQDOxgPs2ZmfPeZtuyNvzt57rPqDjF1iA3vzNgmGmjt4HMZmbszb9sxwZ8+5tBsHeJITG3iOlUkwHHuGzy9m0rxthxMMbuSYAbUwJzZI5JhJMDYcxqOF/RtEy/03ZgUHeOoTG+TfENLCA7OFx4zhAM9hoC08BLQc5imTnHPusOGGMznGEmd4jhu38aQVWyQcw62Fvf/4Nok3ZYflDY6fMfxQ2VMt289+eOONDzW4tYAAEzxyGHuAsQNiJODVAFT4A878gUfZKBgFo2AUjFgAAFsJT6mAedK+AAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Tianjin Agricultural University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Yunchen\",\"middleName\":\"\",\"lastName\":\"Tian\",\"suffix\":\"\"},{\"id\":587612360,\"identity\":\"5aa682a3-46e1-4405-ae99-c3934407d3ec\",\"order_by\":2,\"name\":\"Jianing Quan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Tianjin Agricultural University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jianing\",\"middleName\":\"\",\"lastName\":\"Quan\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-12-31 03:38:14\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-8485463/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-8485463/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1007/s00371-026-04456-4\",\"type\":\"published\",\"date\":\"2026-04-27T15:57:04+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":108438685,\"identity\":\"7a033163-55d3-4a4a-b5c0-dcebfa9c285d\",\"added_by\":\"auto\",\"created_at\":\"2026-05-04 16:10:25\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":29496836,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8485463/v1_covered_c9abc0a6-feb4-4d90-a6d2-55ab0d15357b.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"DiffFish: A Unified Diffusion Model for Robust Multi-Object Fish Tracking in Aquaculture\",\"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\":\"info@researchsquare.com\",\"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\":\"Multi-object fish tracking, Diffusion model, Frame-skipping Learning, Dynamic object insertion\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-8485463/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-8485463/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eIn aquaculture, precise monitoring of fish behavior is crucial for breeding superior strains. 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