DisCoMesh: Efficient and Flexible Artist-Mesh Generation via Sparse Computation powered Discrete Diffusion

Meshes used in games and interactive 3D applications require not only accurate geometry, but also clean topology, fine details, and editable semantic components. However, existing generative methods struggle to produce such assets within a practical computational budget. To address this challenge, we introduce DisCoMesh, a framework based on the view that a multi-part artist mesh is better represented as a set of parts coupled by sparse global relationships rather than as a single global sequence or an ordered sequence of parts. Each semantic part is canonicalized and quantized independently using the full coordinate vocabulary, preserving local geometric detail across parts of different scales. A shared discrete diffusion model then denoises all parts simultaneously, removing the need for an artificial part-generation order. To coordinate simultaneous part generation, we introduce a global interaction module that integrates part placement and global geometric context with sparse token-level communication across parts, preserving coherent connections and spatial relationships. This part-wise formulation enables flexible control over parts, supporting selective part regeneration while preserving the rest of the mesh. Experiments demonstrate that DisCoMesh outperforms existing methods in generation quality, maintains competitive inference speed, and supports diverse downstream applications.