用扩散模型修复文物3D点云，提升古迹复原精度。
Cultural Heritage 3D Reconstruction with Diffusion Networks
- 基于条件扩散模型重建文物3D点云
- 在文化遗迹场景中准确还原几何形态
- 适合从事文物数字化与AI修复的研究者
本文探索了近期生成式AI算法在修复文化遗产物体中的应用，采用一种条件扩散模型，有效重建3D点云。研究评估了该模型在通用与文化遗产特定场景下的表现。结果表明，在考虑物体多样性的情况下，扩散模型能够准确复现文化遗产的几何结构。尽管面临数据多样性与异常值敏感性等挑战，该模型在文物修复研究中展现出显著潜力。本工作为利用AI技术推进古代文物修复方法学奠定了基础。
原文摘要 · Abstract (English)
This article explores the use of recent generative AI algorithms for repairing cultural heritage objects, leveraging a conditional diffusion model designed to reconstruct 3D point clouds effectively. Our study evaluates the model's performance across general and cultural heritage-specific settings. Results indicate that, with considerations for object variability, the diffusion model can accurately reproduce cultural heritage geometries. Despite encountering challenges like data diversity and outlier sensitivity, the model demonstrates significant potential in artifact restoration research. This work lays groundwork for advancing restoration methodologies for ancient artifacts using AI technologies.
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