CVMar 18, 2024

GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulation

arXiv:2403.11990v19 citationsh-index: 14
Originality Highly original
AI Analysis

This addresses the challenge of efficient and intuitive mesh generation and manipulation for industrial 3D asset creation, representing a significant advancement over previous models.

The paper tackles the problem of time-consuming and labor-intensive mesh creation and manipulation by proposing GetMesh, a controllable generative model that generates meshes with rich and sharp details, outperforming single-category and multi-category counterparts, and enables fine-grained control over global/local topologies, part addition/removal, and cross-category part combination.

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, mesh creation and manipulation is often time-consuming and labor-intensive. In this paper, we propose a highly controllable generative model, GetMesh, for mesh generation and manipulation across different categories. By taking a varying number of points as the latent representation, and re-organizing them as triplane representation, GetMesh generates meshes with rich and sharp details, outperforming both single-category and multi-category counterparts. Moreover, it also enables fine-grained control over the generation process that previous mesh generative models cannot achieve, where changing global/local mesh topologies, adding/removing mesh parts, and combining mesh parts across categories can be intuitively, efficiently, and robustly accomplished by adjusting the number, positions or features of latent points. Project page is https://getmesh.github.io.

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