An AIGC-Driven Methodological Framework for Authenticity-Oriented Digital Reconstruction of Historic Buildings: A Case Study of Xiangxian Hall in Lanxi, Zhejiang

Historic buildings are important carriers of traditional Chinese culture; however, they currently face the dual challenges of long-term deterioration and inappropriate interventions. In Zhejiang Province, more than 75,000 immovable cultural heritage sites have been incorporated into the protection system, while a large number of historic buildings remain in urgent need of conservation. In response to the complexity of conventional digital reconstruction processes and the low efficiency of authenticity-oriented restoration, this study proposes an AI-generated content (AIGC)-driven Methodological Framework for efficient and authenticity-oriented digital reconstruction of historic buildings. Taking Xiangxian Hall in Changle Village, Lanxi, Zhejiang, as a case study, this research follows authenticity-oriented criteria, including accurate morphological characteristics, realistic materials and textures, realistic color and light–shadow effects representation, precise proportion and scale, and comprehensive historical and cultural representation. Based on these criteria, a systematic evaluation framework for authenticity-oriented digital reconstruction is established. Furthermore, an AIGC-driven full-process Methodological Framework is proposed that integrates intelligent knowledge retrieval, cross-modal generation models, AI-assisted image-based 3D reconstruction, and inverse rendering. The results demonstrate that the proposed approach, supported by AIGC technologies, can deeply integrate multi-source information, including field investigation data, the existing conditions of historic buildings, and historical and cultural context, thereby achieving efficient and authenticity-oriented digital reconstruction of historic buildings. Furthermore, it provides an integrated technical pathway and practical solution for the conservation and digital inheritance of historic buildings.

Authors

Institutions

Publication Details

Journal
Buildings
Published
2026-09-29
DOI
https://doi.org/10.3390/buildings16193881
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

An AIGC-Driven Methodological Framework for Authenticity-Oriented Digital Reconstruction of Historic Buildings: A Case Study of Xiangxian Hall in Lanxi, Zhejiang

Tao Chen, Pan Kexin, Meng Sun, Yanying Liang et al.
Buildings
3D Surveying and Cultural Heritage
article

An AIGC-Driven Methodological Framework for Authenticity-Oriented Digital Reconstruction of Historic Buildings: A Case Study of Xiangxian Hall in Lanxi, Zhejiang

Tao Chen, Pan Kexin, Meng Sun, Yanying Liang, Xu An
article en

Abstract

Historic buildings are important carriers of traditional Chinese culture; however, they currently face the dual challenges of long-term deterioration and inappropriate interventions. In Zhejiang Province, more than 75,000 immovable cultural heritage sites have been incorporated into the protection system, while a large number of historic buildings remain in urgent need of conservation. In response to the complexity of conventional digital reconstruction processes and the low efficiency of authenticity-oriented restoration, this study proposes an AI-generated content (AIGC)-driven Methodological Framework for efficient and authenticity-oriented digital reconstruction of historic buildings. Taking Xiangxian Hall in Changle Village, Lanxi, Zhejiang, as a case study, this research follows authenticity-oriented criteria, including accurate morphological characteristics, realistic materials and textures, realistic color and light–shadow effects representation, precise proportion and scale, and comprehensive historical and cultural representation. Based on these criteria, a systematic evaluation framework for authenticity-oriented digital reconstruction is established. Furthermore, an AIGC-driven full-process Methodological Framework is proposed that integrates intelligent knowledge retrieval, cross-modal generation models, AI-assisted image-based 3D reconstruction, and inverse rendering. The results demonstrate that the proposed approach, supported by AIGC technologies, can deeply integrate multi-source information, including field investigation data, the existing conditions of historic buildings, and historical and cultural context, thereby achieving efficient and authenticity-oriented digital reconstruction of historic buildings. Furthermore, it provides an integrated technical pathway and practical solution for the conservation and digital inheritance of historic buildings.

BuildingsVol. 16(19)
Zhejiang Normal University (CN), Xingzhi College Zhejiang Normal University
Sustainable cities and communities
Openalex Percentile: Top 9%
3D Surveying and Cultural Heritage
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.