New SOTA mesh generation method uses triangle strips for artist-quality results

Researchers have introduced a new framework called Strips as Tokens (SATO) for generating artist-quality meshes using autoregressive transformers. SATO employs a novel token ordering strategy inspired by triangle strips, which preserves organized edge flow and semantic layout crucial for high-quality modeling. This approach allows for a unified representation that can be decoded into either triangle or quadrilateral meshes, facilitating joint training on diverse datasets. Experiments show SATO surpasses existing methods in geometric quality and structural coherence. AI

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IMPACT Introduces a new method for generating higher-quality 3D meshes, potentially improving workflows in digital art and game development.

RANK_REASON This is a research paper detailing a novel framework for mesh generation. [lever_c_demoted from research: ic=1 ai=1.0]

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• SATO
• arXiv
• Rui Xu

• paper
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