Topology Sculptor, Shape Refiner: Discrete Diffusion Model for High-Fidelity 3D Meshes Generation
Kaiyu Song, Hanjiang Lai, Yaqing Zhang, Chuangjian Cai, Yan Pan Kun Yue, Jian Yin

TL;DR
This paper presents Topology Sculptor, Shape Refiner (TSSR), a novel discrete diffusion model for high-fidelity 3D mesh generation that enables parallel, efficient, and artist-style mesh creation with enhanced control and realism.
Contribution
TSSR introduces a decoupled training and hybrid inference framework, an improved hourglass architecture with bidirectional attention and rotational positional embeddings, and a new connection loss for topological constraints.
Findings
Achieves high-quality meshes with up to 10,000 faces.
Demonstrates effective parallel generation of 3D meshes.
Outperforms existing methods in mesh realism and fidelity.
Abstract
In this paper, we introduce Topology Sculptor, Shape Refiner (TSSR), a novel method for generating high-quality, artist-style 3D meshes based on Discrete Diffusion Models (DDMs). Our primary motivation for TSSR is to achieve highly accurate token prediction while enabling parallel generation, a significant advantage over sequential autoregressive methods. By allowing TSSR to "see" all mesh tokens concurrently, we unlock a new level of efficiency and control. We leverage this parallel generation capability through three key innovations: 1) Decoupled Training and Hybrid Inference, which distinctly separates the DDM-based generation into a topology sculpting stage and a subsequent shape refinement stage. This strategic decoupling enables TSSR to effectively capture both intricate local topology and overarching global shape. 2) An Improved Hourglass Architecture, featuring bidirectional…
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Taxonomy
Topics3D Shape Modeling and Analysis · Face recognition and analysis · Generative Adversarial Networks and Image Synthesis
