Pseudo-Segmentation Guided Detection Refinement for Remote Sensing Small Object Tracking

Pseudo-Segmentation Guided Detection Refinement for Remote Sensing Small Object Tracking | 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 Pseudo-Segmentation Guided Detection Refinement for Remote Sensing Small Object Tracking Chenyang Yan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8181069/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Feb, 2026 Read the published version in Signal, Image and Video Processing → Version 1 posted 5 You are reading this latest preprint version Abstract Multi-object tracking (MOT) shines in the fields of remote sensing video processing and signal analysis. However, the dense and small objects of interest are prone to the failure of generic detection models and tracking strategies, thereby causing missing targets and ambiguous association. To address this issue, we propose the Pseudo-Segmentation guided detection refinement (PSTracker) for small objects in remote sensing tracking scenarios. Specifically, we introduce the simple yet effective pseudo-segmentation module to augment and improve localization information without complex pixel-level annotation. Subsequently, we present the additional long-term predictions which pose shape constraints on the matching conditions to accurately recall tracked targets with the large motion displacement. Additionally, we propose the corresponding multi-task joint learning to optimize the detection and pseudo-segmentation branches. Experimental results on two remote sensing benchmarks achieve the state-of-the-art performance in terms of the detection and association capabilities, which demonstrate the effectiveness and robustness of our tracker. Multi-object tracking Tracklet association Tracking-by-detection Remote sensing images Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Feb, 2026 Read the published version in Signal, Image and Video Processing → Version 1 posted Reviewers agreed at journal 08 Dec, 2025 Reviewers invited by journal 03 Dec, 2025 Editor assigned by journal 25 Nov, 2025 Submission checks completed at journal 25 Nov, 2025 First submitted to journal 22 Nov, 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8181069","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":555109329,"identity":"c5d6a60b-00e5-4025-b3b9-668b147f3d4e","order_by":0,"name":"Chenyang Yan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYNACg3889scbGx9+IF5LxQE5hjOHm40liNdy5oAxw430NgEeopx0/OzBz7xtdxIbZz5sY5BgsJPTbSCk5UxesjRv27PEZunEtgcFDMnGZgcIaTmQY8bM28ac2Cad2G4gwXAgcRtBLeffQLT0SB5sk+AhSssNoC08Zw4bS0gwEqlF8sYbY8k5FWlyBjyJwEA2IMIvfOdzDD+8MbDhMWA//vDhhwo7OYJaFIAKmBDRYUBAOQjINzAwMP4gQuEoGAWjYBSMYAAAtRlF/ZcBK5cAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai University","correspondingAuthor":true,"prefix":"","firstName":"Chenyang","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2025-11-22 14:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8181069/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8181069/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11760-026-05187-8","type":"published","date":"2026-02-19T15:58:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":97894658,"identity":"c0fe96c8-d76f-424c-aa1d-3f40bdd5ee18","added_by":"auto","created_at":"2025-12-10 15:32:52","extension":"json","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2923,"visible":true,"origin":"","legend":"","description":"","filename":"95f3e471186d498bac0b45953718fe12.json","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/16a6af5051bfcbc3fd4f5c4d.json"},{"id":97736361,"identity":"bfba1e74-5c8d-4c2b-8da4-f997a60424f2","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"xml","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":73970,"visible":true,"origin":"","legend":"","description":"","filename":"95f3e471186d498bac0b45953718fe121enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/bf1d18ee88c42361079b3bf1.xml"},{"id":97736360,"identity":"59760c5a-83c2-43b3-b3cf-d011dbdda359","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23782,"visible":true,"origin":"","legend":"","description":"","filename":"2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/73a38a54793badd7dc3eaa66.pdf"},{"id":97736367,"identity":"0f68d60e-5c0c-4123-b147-656d56d69776","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12860,"visible":true,"origin":"","legend":"","description":"","filename":"3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/2533956cb1ca99732c3e158e.pdf"},{"id":97895620,"identity":"c30e429b-b075-4b80-9170-48f956472cd1","added_by":"auto","created_at":"2025-12-10 15:34:34","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":131055,"visible":true,"origin":"","legend":"","description":"","filename":"4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/a61a6a8c8570577726461528.pdf"},{"id":97736363,"identity":"e2a1b128-03e5-46fe-9064-ebd3d89c3a75","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":49689,"visible":true,"origin":"","legend":"","description":"","filename":"5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/0aea49ab8ca1bd462be6c64b.pdf"},{"id":97736364,"identity":"fd1822c8-a45a-439d-a8d5-170b94483b22","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47168,"visible":true,"origin":"","legend":"","description":"","filename":"6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/6c101a5f7dc0447682c37034.pdf"},{"id":97896492,"identity":"20ae5128-87ed-41c1-80df-339b178e75dd","added_by":"auto","created_at":"2025-12-10 15:36:38","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":67871,"visible":true,"origin":"","legend":"","description":"","filename":"CoverLetter.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/177f70e0b8b598a70623e2d7.pdf"},{"id":97736370,"identity":"fab58ef6-63fe-4421-b8c5-c1f63824e6ba","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1871261,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/5460fa22b122861420a0bbba.pdf"},{"id":97736368,"identity":"bf5bfffe-cadb-40ed-b511-8d1ef72def43","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"cls","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":55869,"visible":true,"origin":"","legend":"","description":"","filename":"snjnl.cls","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/beeabf509b45cd7cdd04de5a.cls"},{"id":97896099,"identity":"0c1742a7-b1fa-4e46-91bc-b40dc54f808d","added_by":"auto","created_at":"2025-12-10 15:35:53","extension":"bst","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64166,"visible":true,"origin":"","legend":"","description":"","filename":"snmathphysnum.bst","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/19cb2e579f4c987323058e84.bst"},{"id":97736369,"identity":"1e83f223-adfd-4aa8-b504-5bf7f695c9a4","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80611,"visible":true,"origin":"","legend":"","description":"","filename":"95f3e471186d498bac0b45953718fe121structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/3d3caed250c3c32ea6ca5a21.xml"},{"id":97736372,"identity":"d4d47984-9211-4f4f-912f-f0b3e99be17f","added_by":"auto","created_at":"2025-12-08 19:38:51","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":87168,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1/c97d297d7e450243a4eb3734.html"},{"id":103252212,"identity":"7cbc880b-870f-417c-a921-1e6ea3704ced","added_by":"auto","created_at":"2026-02-23 16:13:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1785619,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8181069/v1_covered_cb116138-25fc-4613-94fc-1acb7bf2e2f3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pseudo-Segmentation Guided Detection Refinement for Remote Sensing Small Object Tracking","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":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Multi-object tracking, Tracklet association, Tracking-by-detection, Remote sensing images","lastPublishedDoi":"10.21203/rs.3.rs-8181069/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8181069/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMulti-object tracking (MOT) shines in the fields of remote sensing video processing and signal analysis. However, the dense and small objects of interest are prone to the failure of generic detection models and tracking strategies, thereby causing missing targets and ambiguous association. To address this issue, we propose the Pseudo-Segmentation guided detection refinement (PSTracker) for small objects in remote sensing tracking scenarios. Specifically, we introduce the simple yet effective pseudo-segmentation module to augment and improve localization information without complex pixel-level annotation. Subsequently, we present the additional long-term predictions which pose shape constraints on the matching conditions to accurately recall tracked targets with the large motion displacement. Additionally, we propose the corresponding multi-task joint learning to optimize the detection and pseudo-segmentation branches. Experimental results on two remote sensing benchmarks achieve the state-of-the-art performance in terms of the detection and association capabilities, which demonstrate the effectiveness and robustness of our tracker.\u003c/p\u003e","manuscriptTitle":"Pseudo-Segmentation Guided Detection Refinement for Remote Sensing Small Object Tracking","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 19:38:47","doi":"10.21203/rs.3.rs-8181069/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"157876976319966377979781671734743526966","date":"2025-12-08T07:21:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-04T04:58:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-25T14:36:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-25T14:35:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Signal, Image and Video Processing","date":"2025-11-22T14:26:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3a266d49-8dfd-4e07-a9ce-2009f31bbce1","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:07:54+00:00","versionOfRecord":{"articleIdentity":"rs-8181069","link":"https://doi.org/10.1007/s11760-026-05187-8","journal":{"identity":"signal-image-and-video-processing","isVorOnly":false,"title":"Signal, Image and Video Processing"},"publishedOn":"2026-02-19 15:58:37","publishedOnDateReadable":"February 19th, 2026"},"versionCreatedAt":"2025-12-08 19:38:47","video":"","vorDoi":"10.1007/s11760-026-05187-8","vorDoiUrl":"https://doi.org/10.1007/s11760-026-05187-8","workflowStages":[]},"version":"v1","identity":"rs-8181069","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8181069","identity":"rs-8181069","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}