Mesh repair is a long-standing challenge in computer graphics and related fields. Converting defective meshes into watertight manifold meshes can greatly benefit downstream applications such as geometric processing, simulation, fabrication, learning, and synthesis. In this work, we first introduce three visual measures for visibility, orientation, and openness, based on ray-tracing. We then present a novel mesh repair framework that incorporates visual measures with several critical steps, i.e., open surface closing, face reorientation, and global optimization, to effectively repair defective meshes, including gaps, holes, self-intersections, degenerate elements, and inconsistent orientations. Our method reduces unnecessary mesh complexity without compromising geometric accuracy or visual quality while preserving input attributes such as UV coordinates for rendering. We evaluate our approach on hundreds of models randomly selected from ShapeNet and Thingi10K, demonstrating its effectiveness and robustness compared to existing approaches.

翻译：网格修复是计算机图形学及相关领域中一个长期存在的挑战。将有缺陷的网格转换为水密流形网格，能够极大地惠及下游应用，例如几何处理、仿真、制造、学习与合成。本文首先基于光线追踪引入了三个视觉度量指标，分别用于评估可见性、朝向与开敞度。随后，我们提出了一种新颖的网格修复框架，该框架将视觉度量与若干关键步骤（即开放表面闭合、面片重定向及全局优化）相结合，以有效修复存在间隙、孔洞、自交、退化单元及朝向不一致等缺陷的网格。我们的方法在保持输入属性（如用于渲染的UV坐标）的同时，降低了不必要的网格复杂度，且不影响几何精度或视觉质量。我们在从ShapeNet和Thingi10K中随机选取的数百个模型上评估了该方法，结果表明，与现有方法相比，我们的方法更具有效性与鲁棒性。