mlsanityData to 14 Oct 2026

GenUDC: High Quality 3D Mesh Generation with Unsigned Dual Contouring Representation

arXiv 2410.17802 ↗First posted 23 Oct 2024cs.CV cs.GRcited by 3

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Abstract (arXiv)

Generating high-quality meshes with complex structures and realistic surfaces is the primary goal of 3D generative models. Existing methods typically employ sequence data or deformable tetrahedral grids for mesh generation. However, sequence-based methods have difficulty producing complex structures with many faces due to memory limits. The deformable tetrahedral grid-based method MeshDiffusion fails to recover realistic surfaces due to the inherent ambiguity in deformable grids. We propose the GenUDC framework to address these challenges by leveraging the Unsigned Dual Contouring (UDC) as the mesh representation. UDC discretizes a mesh in a regular grid and divides it into the face and vertex parts, recovering both complex structures and fine details. As a result, the one-to-one mapping between UDC and mesh resolves the ambiguity problem. In addition, GenUDC adopts a two-stage, coarse-to-fine generative process for 3D mesh generation. It first generates the face part as a rough shape and then the vertex part to craft a detailed shape. Extensive evaluations demonstrate the superiority of UDC as a mesh representation and the favorable performance of GenUDC in mesh generation. The code and trained models are available at https://github.com/TrepangCat/GenUDC.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 45 of its 76 references that are in the map. First posted on arXiv 23 Oct 2024.

Builds on

45 of 76 references.

References · 45

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33 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025QEMesh: Employing A Quadric Error Metrics-Based Representation for Mesh Generationcited by 0
  2. 2026Dehallu3D: Hallucination-Mitigated 3D Generation from Single Image via Cyclic View Consistency Refinementcited by 0
  3. 2026DiffGI: Differentiable Geometry Images for High-Fidelity Thin-Shell 3D Generationcited by 0