忠实等值线化：摆脱等值面的近无损三维体素表示
Faithful Contouring: Near-Lossless 3D Voxel Representation Free from Iso-surface
提供一种不依赖等值面提取的稀疏体素化表示，可直接把任意网格编码为 2048+ 分辨率的近无损体素，并配套双模式自编码器；对做三维生成、重建的视觉研究者，可作为替代 iso-surface / 隐式场的形状表示与重建骨干。
原文依据 a sparse voxelized representation that supports 2048+ resolutions for arbitrary meshes
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论精确且高效的三维网格体素化表示是三维重建与生成的基础。然而，现有基于等值面的表示严重依赖水密化处理或渲染优化，这不可避免地损害了几何保真度。我们提出忠实等值线化（Faithful Contouring），一种支持任意网格 2048 以上分辨率的稀疏体素化表示，既不需要将网格转换为场函数，也不需要在重网格化过程中提取等值面。它通过保留锐利特征与内部结构实现近无损保真度，即使面对几何与拓扑复杂的困难情形亦然。所提方法在纹理化、操控与编辑方面也展现出灵活性。在表示之外，我们为忠实等值线化设计了一个双模式自编码器，从而实现可扩展且保留细节的形状重建。大量实验表明，忠实等值线化在表示与重建两方面均以更高的精度和效率超越现有方法。在直接表示方面，其距离误差达到 10^-5 量级；在网格重建方面，相比强基线，倒角距离降低 93%，F 值提升 35%，证实其作为三维学习任务表示的优越保真度。
英文原文摘要 1304 字符
Accurate and efficient voxelized representations of 3D meshes are the foundation of 3D reconstruction and generation. However, existing representations based on iso-surface heavily rely on water-tightening or rendering optimization, which inevitably compromise geometric fidelity. We propose Faithful Contouring, a sparse voxelized representation that supports 2048+ resolutions for arbitrary meshes, requiring neither converting meshes to field functions nor extracting the isosurface during remeshing. It achieves near-lossless fidelity by preserving sharpness and internal structures, even for challenging cases with complex geometry and topology. The proposed method also shows flexibility for texturing, manipulation, and editing. Beyond representation, we design a dual-mode autoencoder for Faithful Contouring, enabling scalable and detail-preserving shape reconstruction. Extensive experiments show that Faithful Contouring surpasses existing methods in accuracy and efficiency for both representation and reconstruction. For direct representation, it achieves distance errors at the 10^ -5 level; for mesh reconstruction, it yields a 93% reduction in Chamfer Distance and a 35% improvement in F-score over strong baselines, confirming superior fidelity as a representation for 3D learning tasks.