论文标题
时尚图像设计的基于深度学习的互动素描系统
A deep learning based interactive sketching system for fashion images design
论文作者
论文摘要
在这项工作中，我们提出了一个交互式系统，以从时尚草图和纹理信息中设计各种高质量的服装图像。该系统背后的主要挑战是根据用户提供的纹理信息生成高质量和详细的纹理。先前的工作主要使用纹理补丁表示，并尝试将小纹理补丁映射到整个服装图像中，因此无法生成高质量的细节。相比之下，受固有图像分解的启发，我们将此任务分解为纹理合成和阴影增强。特别是，我们提出了一种新颖的双色边缘纹理表示，以合成纹理的服装图像和一个基于灰度边缘呈现阴影的阴影增强剂。双色边缘表示提供了简单但有效的纹理提示和颜色约束，因此可以更好地重建细节。此外，随着渲染的阴影，合成的服装图像变得更加生动。
In this work, we propose an interactive system to design diverse high-quality garment images from fashion sketches and the texture information. The major challenge behind this system is to generate high-quality and detailed texture according to the user-provided texture information. Prior works mainly use the texture patch representation and try to map a small texture patch to a whole garment image, hence unable to generate high-quality details. In contrast, inspired by intrinsic image decomposition, we decompose this task into texture synthesis and shading enhancement. In particular, we propose a novel bi-colored edge texture representation to synthesize textured garment images and a shading enhancer to render shading based on the grayscale edges. The bi-colored edge representation provides simple but effective texture cues and color constraints, so that the details can be better reconstructed. Moreover, with the rendered shading, the synthesized garment image becomes more vivid.
