DiffAvatar: Simulation-Ready Garment Optimization with Differentiable Simulation
Yifei Li, Hsiao-Yu Chen, Egor Larionov, Nikolaos Sarafianos, Wojciech Matusik, Tuur Stuyck
Abstract
Figure 1 . We present DiffAvatar, an automated computational method to recover simulation-ready garment and body assets. Starting from a multi-view capture, we reconstruct a semantically segmented 3D mesh. The segmented clothing geometry acts as a target shape for our optimization pipeline. Our method recovers body shape and pose, clothing pattern and clothing material parameters from a single scan. We optimize a clothing template in 2D pattern space to reproduce the captured clothing in 3D in a physical way. We compute gradients of required parameters using a differentiable simulation approach.
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