将中世纪手稿插图转为可交互的3D模型，支持触觉打印与虚拟展示。
A Semi-Automated Framework for 3D Reconstruction of Medieval Manuscript Miniatures
- 结合分割、生成与人工精修，实现从2D插图到3D模型的半自动化流程。
- Hi3DGen在几何保真度与表面细节间取得平衡，适合作为初始模型。
- 成果可用于网页XR、增强现实叠加及视障者触觉打印，跨艺术风格通用。
本文提出一种半自动化框架，将中世纪手稿中的二维插图转化为适用于扩展现实（XR）、触觉3D打印和基于网络的可视化三维数字模型。我们在两个典藏的69幅手绘图像上评估了七种图像转3D方法（TripoSR、SF3D、SPAR3D、TRELLIS、Wonder3D、SAM~3D、Hi3DGen），采用基于渲染的指标（轮廓交并比、LPIPS、CLIP~Score）和体素度量（深度范围比、封闭率）进行评估，发现体积膨胀与几何保真度之间存在权衡。其中，Hi3DGen通过法向桥接方法，在拓扑质量与丰富表面细节间达到较好平衡，适合作为专家精修的起点。该流程包括SAM分割、Hi3DGen网格生成、ZBrush中的人工精修及AI辅助贴图。通过对梵蒂冈图书馆《格拉蒂安教令集》哥特式彩绘和朱利奥·克洛维奥文艺复兴时期小插图的两个案例研究，验证了其在不同艺术传统下的适用性。生成的模型可用于WebXR可视化、物理手稿上的增强现实叠加，以及视障用户的触觉3D打印。
原文摘要 · Abstract (English)
This paper presents a semi-automated framework for transforming two-dimensional miniatures from medieval manuscripts into three-dimensional digital models suitable for extended reality (XR), tactile 3D~printing, and web-based visualization. We evaluate seven image-to-3D methods (TripoSR, SF3D, SPAR3D, TRELLIS, Wonder3D, SAM~3D, Hi3DGen) on 69~manuscript figures from two collections using rendering-based metrics (Silhouette IoU, LPIPS, CLIP~Score) and volumetric measures (Depth Range Ratio, watertight percentage), revealing a trade-off between volumetric expansion and geometric fidelity. Hi3DGen balances topological quality with rich surface detail through its normal bridging approach, making it a good starting point for expert refinement. Our pipeline combines SAM segmentation, Hi3DGen mesh generation, expert refinement in ZBrush, and AI-assisted texturing. Two case studies on Gothic illuminations from the Decretum Gratiani (Vatican Library) and Renaissance miniatures by Giulio Clovio demonstrate applicability across artistic traditions. The resulting models can support WebXR visualization, AR overlay on physical manuscripts, and tactile 3D~prints for visually impaired users.
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