@inproceedings{
wang2024genudc,
title={Gen{UDC}: High Quality 3D Mesh Generation With Unsigned Dual Contouring Representation},
author={Ruowei Wang and Jiaqi Li and Dan Zeng and Xueqi Ma and Xu Zixiang and Jianwei Zhang and Qijun Zhao},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=5wLf2MWReq}
}
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 novel GenUDC framework to address these challenges, leveraging the Unsigned Dual Contouring (UDC) as a better 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 will be released upon publication.
GenUDC: High Quality 3D Mesh Generation With Unsigned Dual Contouring Representation
Ruowei Wang Jiaqi Li Dan Zeng Xueqi Ma Xu Zixiang Jianwei Zhang Qijun Zhao