The Dunhuang Mogao Grottoes are among the most significant historical and cultural sites in China, with the Dunhuang Mural serving as key representative artifacts. Due to natural erosion, human activities, and other factors, it is crucial to protect these frescoes authentically and accurately to ensure their preservation. To address this, we propose a technological framework, 3DSynBrush, for high-quality 3D reconstruction of Chinese painting data. First, single elements are extracted from the mural through the Perspective-Driven Synthesis (PDS) Module, and a sparse perspective is generated. The sparse view is then passed through the Neural Rendering Synthesizer to obtain a continuous view image, which ultimately meets the input requirements of the Light Field Fusion Meshing Module to achieve 3D reconstruction. 3DSynBrush aims to reconstruct a realistic model of the scene depicted using only a single primary view of the fresco. Moreover, we develope a high-quality Chinese Mural Elements dataset, termed CME. Compared to current 3D reconstruction algorithms, 3DSynBrush produces visually coherent results while using only 40% of the vertices and triangles, thereby minimizing computational resources.
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Xianlin Peng
Jingyu Wang
Qiyao Hu
Northwest University
Beijing Academy of Artificial Intelligence
State Administration of Cultural Heritage
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Peng et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69b79da78166e15b153aaeaa — DOI: https://doi.org/10.1038/s40494-026-02424-8
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