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DiT-Garment: Garment Dynamics with Diffusion Transformers
We present DiT-Garment to model dynamic 3D clothing over human body models in arbitrary motion. Unlike existing methods, DiT-Garment can animate garments with unseen designs and physical materials, while allowing for direct inference of deformations for any target pose. To achieve this, we leverage a 2D diffusion transformer architecture to learn 3D deformations in a 2D UV-space. As the result is non-deterministic, our generative model learns the distribution of possible outcomes. The template garment is represented as a 3D triangle mesh spatially aligned with a 3D human body model in a standa
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T11:44:03.000Z
First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.