Faithful Contouring: Near-Lossless 3D Voxel Representation Free from Iso-surface

• URL: http://arxiv.org/abs/2511.04029v3
• Date: Thu, 13 Nov 2025 01:45:21 GMT
• Title: Faithful Contouring: Near-Lossless 3D Voxel Representation Free from Iso-surface
• Authors: Yihao Luo, Xianglong He, Chuanyu Pan, Yiwen Chen, Jiaqi Wu, Yangguang Li, Wanli Ouyang, Yuanming Hu, Guang Yang, ChoonHwai Yap,
• Abstract summary: We propose Faithful Contouring, a voxelized representation that achieves near-lossless fidelity in 3D meshes.<n>The proposed method also shows flexibility and improvement for existing representation.
• Score: 49.742538510885
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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