MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh
  Tokenization
Authors: name: Yiwen Chen, name: Yikai Wang, name: Yihao Luo, name: Zhengyi Wang, name: Zilong Chen, name: Jun Zhu, name: Chi Zhang, name: Guosheng Lin

We introduce MeshAnything V2, an autoregressive transformer that generates
Artist-Created Meshes (AM) aligned to given shapes. It can be integrated with
various 3D asset production pipelines to achieve high-quality, highly
controllable AM generation. MeshAnything V2 surpasses previous methods in both
efficiency and performance using models of the same size. These improvements
are due to our newly proposed mesh tokenization method: Adjacent Mesh
Tokenization (AMT). Different from previous methods that represent each face
with three vertices, AMT uses a single vertex whenever possible. Compared to
previous methods, AMT requires about half the token sequence length to
represent the same mesh in average. Furthermore, the token sequences from AMT
are more compact and well-structured, fundamentally benefiting AM generation.
Our extensive experiments show that AMT significantly improves the efficiency
and performance of AM generation. Project Page:
https://buaacyw.github.io/meshanything-v2/