Realistic reconstruction of 3D clothing from an image has wide applications, such as avatar creation and virtual try-on. This paper presents a novel framework that reconstructs the texture map for 3D garments from a single image with pose. Assuming that 3D garments are modeled by stitching 2D garment sewing patterns, our specific goal is to generate a texture image for the sewing patterns. A key component of our framework, the Texture Unwarper, infers the original texture image from the input clothing image, which exhibits warping and occlusion of texture due to the user's body shape and pose. The Texture Unwarper effectively transforms between the input and output images by mapping the latent spaces of the two images. By inferring the unwarped original texture of the input garment, our method helps reconstruct 3D garment models that can show high-quality texture images realistically deformed for new poses. We validate the effectiveness of our approach through a comparison with other methods and ablation studies.

翻译：从图像中逼真重建三维服装在虚拟化身创建和虚拟试穿等领域具有广泛应用。本文提出一种新颖框架，可从包含姿态的单张图像重建三维服装的纹理贴图。基于三维服装由二维服装纸样缝合而成的假设，本文的具体目标是生成纸样的纹理图像。该框架的核心组件——纹理反变形器（Texture Unwarper），可从因人体体型与姿态产生纹理扭曲及遮挡的输入服装图像中推断原始纹理。该组件通过映射输入图像与输出图像的潜在空间，有效实现两者间的转换。通过推断输入服装的无变形原始纹理，所提方法有助于重建能针对新姿态展现高质量逼真纹理变形效果的三维服装模型。我们通过与其它方法的对比实验及消融研究验证了本方法的有效性。