Improving Real-time 3D Reconstruction and Semantic Segmentation for AR Applications

Improving Real-time 3D Reconstruction and Semantic Segmentation for AR Applications | 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 Improving Real-time 3D Reconstruction and Semantic Segmentation for AR Applications Yu Nong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5796173/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper presents an innovative approach to enhancing real-time 3D reconstruction and semantic segmentation for Augmented Reality (AR) applications using advanced Artificial Intelligence (AI) techniques. We introduce a novel hybrid architecture that combines a lightweight NeRF (Neural Radiance Fields) variant with a real-time semantic segmentation network. Our method achieves state-of-the-art performance in both 3D reconstruction accuracy and semantic understanding while maintaining real-time performance on mobile AR devices. Experimental results demonstrate significant improvements in reconstruction quality, segmentation accuracy, and computational efficiency compared to existing methods. Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-5796173","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":399932244,"identity":"5bef8580-3dd6-462f-a328-a9b5d71fabc4","order_by":0,"name":"Yu Nong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYBADOQZmMG3BwAamC5gJajEGamFsYGCQgGoxIKwlEagcooWBkBaDGwlsDz7uqE3fcJz3+WOeGgl5PgYew8cVBtb4tLAbzjxzPHfDYXbDZp5jEoZtDDzGhmcM0vHaIs3bdix3ZjMbYzMPmwRjGwPvNskGg8MEtaRLgrX8k7AnVktNAj8zUAtvm0QiQS2SZx62Sc5sO2DYD9Qyc26fRHIbM/9nwwY8fuE7nnxM4mNbnTwb/zGGD2++2djOb29LfNhQgTvEFA6AYoMB2RmEIlG+AUzVEVA2CkbBKBgFIxoAAFCASkBMPJDYAAAAAElFTkSuQmCC","orcid":"","institution":"VirtualAI China","correspondingAuthor":true,"prefix":"","firstName":"Yu","middleName":"","lastName":"Nong","suffix":""}],"badges":[],"createdAt":"2025-01-09 11:39:18","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5796173/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5796173/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73441496,"identity":"67f222e9-95b4-4307-b163-d5ce9510ffed","added_by":"auto","created_at":"2025-01-10 03:44:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":255043,"visible":true,"origin":"","legend":"","description":"","filename":"3dandss.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5796173/v1_covered_94f79a1b-e120-432e-bb88-fd9f1bb44938.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eImproving Real-time 3D Reconstruction and Semantic Segmentation for AR Applications\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"VirtualAI China","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5796173/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5796173/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents an innovative approach to enhancing real-time 3D reconstruction and semantic segmentation for Augmented Reality (AR) applications using advanced Artificial Intelligence (AI) techniques. We introduce a novel hybrid architecture that combines a lightweight NeRF (Neural Radiance Fields) variant with a real-time semantic segmentation network. Our method achieves state-of-the-art performance in both 3D reconstruction accuracy and semantic understanding while maintaining real-time performance on mobile AR devices. Experimental results demonstrate significant improvements in reconstruction quality, segmentation accuracy, and computational efficiency compared to existing methods.\u003c/p\u003e","manuscriptTitle":"Improving Real-time 3D Reconstruction and Semantic Segmentation for AR Applications","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-10 03:35:56","doi":"10.21203/rs.3.rs-5796173/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"44b1888a-6df9-4d01-9297-974def5bf37e","owner":[],"postedDate":"January 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-10T03:35:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-10 03:35:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5796173","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5796173","identity":"rs-5796173","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}