CVJan 23

ReWeaver: Towards Simulation-Ready and Topology-Accurate Garment Reconstruction

arXiv:2601.16672v11 citationsh-index: 4
Originality Highly original
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This work addresses the sim-to-real gap for applications like digital avatars and robotic manipulation by providing simulation-ready garment reconstructions, representing a novel method for a known bottleneck.

The paper tackles the problem of 3D garment reconstruction from sparse multi-view RGB images, which often fails to produce accurate topology and sewing structures for physical simulation, and proposes ReWeaver, a framework that predicts seams and panels to achieve structured representations, outperforming existing methods in topology accuracy and geometry alignment.

High-quality 3D garment reconstruction plays a crucial role in mitigating the sim-to-real gap in applications such as digital avatars, virtual try-on and robotic manipulation. However, existing garment reconstruction methods typically rely on unstructured representations, such as 3D Gaussian Splats, struggling to provide accurate reconstructions of garment topology and sewing structures. As a result, the reconstructed outputs are often unsuitable for high-fidelity physical simulation. We propose ReWeaver, a novel framework for topology-accurate 3D garment and sewing pattern reconstruction from sparse multi-view RGB images. Given as few as four input views, ReWeaver predicts seams and panels as well as their connectivities in both the 2D UV space and the 3D space. The predicted seams and panels align precisely with the multi-view images, yielding structured 2D--3D garment representations suitable for 3D perception, high-fidelity physical simulation, and robotic manipulation. To enable effective training, we construct a large-scale dataset GCD-TS, comprising multi-view RGB images, 3D garment geometries, textured human body meshes and annotated sewing patterns. The dataset contains over 100,000 synthetic samples covering a wide range of complex geometries and topologies. Extensive experiments show that ReWeaver consistently outperforms existing methods in terms of topology accuracy, geometry alignment and seam-panel consistency.

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