Summary of Meshanything V2: Artist-created Mesh Generation with Adjacent Mesh Tokenization, by Yiwen Chen et al.
MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization
by Yiwen Chen, Yikai Wang, Yihao Luo, Zhengyi Wang, Zilong Chen, Jun Zhu, Chi Zhang, Guosheng Lin
First submitted to arxiv on: 5 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Graphics (cs.GR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary MeshAnything V2, an advanced mesh generation model, addresses the limitations of previous autoregressive methods by introducing Adjacent Mesh Tokenization (AMT). Unlike traditional approaches that represent each face using three vertices, AMT optimizes this by employing a single vertex wherever feasible. This streamlines the tokenization process and enhances efficiency in generating Artist-Created Meshes that align precisely with specified shapes. The model achieves superior performance without increasing computational costs, effectively doubling the face limit compared to previous models. It has been designed to create meshes that meet specific shape requirements. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MeshAnything V2 is a new way of making 3D shapes called “meshes”. Before, people had to make these shapes by hand, which was very time-consuming. Some researchers tried using computers to make them, but their methods weren’t very good at creating complex shapes. One problem with these old methods was that they were very slow because they didn’t process the information in a smart way. The new method, called MeshAnything V2, fixes this by being more efficient and clever. It can make much more complicated shapes than before without using up too many computer resources. |
Keywords
» Artificial intelligence » Autoregressive » Tokenization
