Garment Particles is a 5D point cloud representation jointly encoding 2D sewing patterns and 3D geometry, supporting rectified flow generation from high-level inputs and diffusion-based editing of patterns or shapes.
Graph.31, 4, Article 36 (July 2012), 11 pages
2 Pith papers cite this work. Polarity classification is still indexing.
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Derives a contact-aware Fisher information measure to synthesize robot behaviors that maximize information-rich contacts for efficient object parameter learning.
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Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing
Garment Particles is a 5D point cloud representation jointly encoding 2D sewing patterns and 3D geometry, supporting rectified flow generation from high-level inputs and diffusion-based editing of patterns or shapes.
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Behavior Synthesis via Contact-Aware Fisher Information Maximization
Derives a contact-aware Fisher information measure to synthesize robot behaviors that maximize information-rich contacts for efficient object parameter learning.