GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulation
Zhaoyang Lyu, Ben Fei, Jinyi Wang, Xudong Xu, Ya Zhang, Weidong Yang,, Bo Dai

TL;DR
GetMesh is a novel controllable generative model for 3D mesh creation and editing, enabling detailed, category-agnostic, and intuitive manipulation of mesh structures through a point-based latent representation.
Contribution
It introduces a flexible point-based latent space and re-organizing technique for high-quality, controllable mesh generation across multiple categories, surpassing existing models.
Findings
Outperforms existing models in detail and quality
Enables intuitive control over mesh topology and parts
Supports cross-category mesh manipulation
Abstract
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,…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Anomaly Detection Techniques and Applications
