Reproduce “MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization” on OpenResearch
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About this paper
Yiwen Chen, Yikai Wang, Yihao Luo, Zhengyi Wang, Zilong Chen, Jun Zhu, Chi Zhang, Guosheng Lin
MeshAnything V2 introduces Adjacent Mesh Tokenization (AMT) to enable the autoregressive generation of more complex artist-created 3D meshes by reducing token sequence length by half. The method improves mesh quality and doubles the maximum generatable face count to 1600, significantly enhancing efficiency and detail in 3D content creation.
Key insights
- Effective mesh tokenization requires a balance between sequence compactness and the regularity/learnability of the token pattern, which AMT achieves by capitalizing on face adjacency.
- Introducing special tokens like '&' (for sequence interruptions) and '$' (for vertex swaps) can significantly enhance token sequence compression and maintain structural integrity during autoregressive generation.
- Directly using discretized coordinates as token indices, rather than relying on an intermediate VQ-VAE, can simplify the generative pipeline and improve accuracy for complex mesh structures.
Summary by alphaXiv.
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