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：从三维人体着装形状生成可仿真服装模型的能力，将显著提升真实服装捕获几何的可解释性及其在虚拟世界中的忠实再现。这一技术将对社交VR中的形状捕获以及时尚产业的虚拟试穿等领域产生重要影响。为符合服装产业标准化建模流程及布料仿真软件的要求，需恢复二维纸样。这涉及逆向服装设计问题，正是本文的研究重点：以任意目标服装几何为起点，本系统通过自动调整对应的二维模板纸样及物理仿真（PBS）的材料参数，估算出可动画化的服装模型。基于可微布料模拟器，优化过程以最小化仿真服装形状与目标几何之间的偏差为导向。此外，我们生成的纸样满足左右对称等制造要求，适用于服装逆向制造。我们通过不同服装类型的实例验证了该方法，证明其能忠实再现悬垂服装形态与缝纫纸样。