AIGC Based Digital Heritage Reconstruction of Qing Interior Canopies

AIGC Based Digital Heritage Reconstruction of Qing Interior Canopies | 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 Article AIGC Based Digital Heritage Reconstruction of Qing Interior Canopies 常青 卫, 洞一 孔, 阳 王, 晶 贾, 家汝 刘 This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7541038/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Jan, 2026 Read the published version in npj Heritage Science → Version 1 posted 11 You are reading this latest preprint version Abstract This study explores the application of Artificial Intelligence Generated Content (AIGC) to the digital reconstruction of Qing-period interior canopy components, a representative form of traditional Chinese timberwork. To address fragmented archives and modeling inefficiency, we propose an integrated workflow combining historical image digitization, semantic lexicon building, prompt design, and image-to-model validation. A 76-term canopy glossary was embedded into a four-layer prompting template, and 312 images were generated across multiple platforms to analyze semantic response patterns and structural deviations. Validation using SketchUp confirmed stylistic fidelity with geometric deviations of only 3–4% and approximately 85% node interpretability. While AIGC excels in stylistic coherence and decorative richness, its limitations in structural logic require expert semantic annotation. Beyond reconstruction, the approach demonstrates potential for developing component ontologies, enriching BIM libraries, and supporting digital heritage conservation through rapid prototyping and stylistic diversity. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Jan, 2026 Read the published version in npj Heritage Science → Version 1 posted Editorial decision: Revision requested 27 Oct, 2025 Reviews received at journal 27 Oct, 2025 Reviews received at journal 14 Oct, 2025 Reviews received at journal 10 Oct, 2025 Reviewers agreed at journal 07 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers invited by journal 17 Sep, 2025 Editor assigned by journal 16 Sep, 2025 Submission checks completed at journal 15 Sep, 2025 First submitted to journal 15 Sep, 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-7541038","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":520160244,"identity":"e20aefea-35be-4aee-9b4b-08b282bbf34e","order_by":0,"name":"常青 卫","email":"","orcid":"","institution":"Institute of Geography, Henan Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"常青","middleName":"","lastName":"卫","suffix":""},{"id":520160245,"identity":"358e3242-e3aa-4d14-bfe3-41a24fc0fe17","order_by":1,"name":"洞一 孔","email":"","orcid":"","institution":"Institute of Geography, Henan Academy of 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