
MeshAnything V2 introduces Adjacent Mesh Tokenization (AMT), a novel method that significantly improves the efficiency and quality of artist-created mesh generation by representing faces with single vertices, resulting in more compact and well-structured token sequences for enhanced sequence learning.


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meshanything-v2-enhancing-artist-created-mesh-generation-efficiency-and-quality-through-adjacent-mesh-tokenization


MeshAnything V2: Enhancing Artist-Created Mesh Generation Efficiency and Quality Through Adjacent Mesh Tokenization


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A novel mesh tokenization method, Blocked and Patchified Tokenization (BPT), significantly compresses mesh data, enabling the training of mesh generation models on larger, more detailed datasets and leading to improved performance and robustness in mesh generation from point clouds and images.


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Blocked and Patchified Tokenization for Scalable Mesh Generation



A continuous representation for manifold polygonal meshes that can be optimized and learned to generate diverse mesh outputs.


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Generating Manifold Surface Meshes with Continuous Connectivity Representations
