We present an automatic and semantic pose and wrinkle transfer method from one garment onto another for aesthetic display, which is previously performed by professional artists using a knowledge-intensive and time-consuming process. Given a source garment model with fine wrinkle details in a specific pose and another target garment model with a similar style in a neutral pose but without fine wrinkle details, our approach can automatically transfer the pose and wrinkle details faithfully from the source to the target using a two-stage process. In the semantic correspondence establishment stage, we construct a dense correspondence between the source and the target by utilizing their semantic information in 2D patterns. Specifically, we first obtain the initial correspondence points on the paired 2D patterns by leveraging their semantic information. These marker points, which act as constraints, are mapped to their corresponding 3D models. We then establish their per-triangle correspondence using a non-rigid Iterative Closest Point (ICP) algorithm. In the deformation transfer stage, we transfer the pose and wrinkle details from the source to the target by solving an optimization problem. Extensive experiments validate that our method is able to generate better results compared to state-of-the-art methods, and it can lead to significant time savings for fashion designers.

我们提出了一种从一件衣服到另一件衣服的自动和语义姿势和皱纹转移方法，用于美学展示，以前由专业艺术家使用知识密集型和耗时的过程进行。给定在特定姿势中具有精细皱纹细节的源服装模型和在中性姿势中具有相似风格但没有精细皱纹细节的另一个目标服装模型，我们的方法可以使用一个两阶段的过程。在语义对应建立阶段，我们利用二维模式中的语义信息构建源和目标之间的密集对应关系。具体来说，我们首先通过利用它们的语义信息来获得配对 2D 模式上的初始对应点。这些充当约束的标记点被映射到它们相应的 3D 模型。然后我们使用非刚性迭代最近点 (ICP) 算法建立它们每个三角形的对应关系。在变形转移阶段，我们通过解决优化问题将姿势和皱纹细节从源转移到目标。大量实验证明，与最先进的方法相比，我们的方法能够产生更好的结果，并且可以为时装设计师节省大量时间。我们通过解决优化问题将姿势和皱纹细节从源转移到目标。大量实验证明，与最先进的方法相比，我们的方法能够产生更好的结果，并且可以为时装设计师节省大量时间。我们通过解决优化问题将姿势和皱纹细节从源转移到目标。大量实验证明，与最先进的方法相比，我们的方法能够产生更好的结果，并且可以为时装设计师节省大量时间。