The capability to generate simulation-ready garment models from 3D shapes of clothed humans will significantly enhance the interpretability of captured geometry of real garments, as well as their faithful reproduction in the virtual world. This will have notable impact on fields like shape capture in social VR, and virtual try-on in the fashion industry. To align with the garment modeling process standardized by the fashion industry as well as cloth simulation softwares, it is required to recover 2D patterns. This involves an inverse garment design problem, which is the focus of our work here: Starting with an arbitrary target garment geometry, our system estimates an animatable garment model by automatically adjusting its corresponding 2D template pattern, along with the material parameters of the physics-based simulation (PBS). Built upon a differentiable cloth simulator, the optimization process is directed towards minimizing the deviation of the simulated garment shape from the target geometry. Moreover, our produced patterns meet manufacturing requirements such as left-to-right-symmetry, making them suited for reverse garment fabrication. We validate our approach on examples of different garment types, and show that our method faithfully reproduces both the draped garment shape and the sewing pattern.

翻译：从3D人体着装形状生成可用于仿真的服装模型的能力，将显著增强对真实服装捕获几何形状的可解释性，以及其在虚拟世界中的忠实再现。这项技术对社会VR中的形状捕获和时尚产业中的虚拟试穿等领域具有重要影响。为符合时尚产业标准化的服装建模流程及布料仿真软件的要求，需要恢复2D纸样。这涉及逆向服装设计问题，即本文的研究重点：从任意目标服装几何形状出发，我们的系统通过自动调整对应的2D模板纸样及物理仿真（PBS）中的材料参数，来估计可动画的服装模型。基于可微布料模拟器，优化过程旨在将模拟服装形状与目标几何之间的偏差最小化。此外，我们生成的纸样满足左-右对称性等制造要求，适用于服装逆向制作。我们通过不同服装类型的示例验证了该方法，结果表明我们的方法能忠实再现褶皱服装形状和裁剪纸样。