Deep learning-based sketch-to-clothing image generation provides the initial designs and inspiration in the fashion design processes. However, clothing generation from freehand drawing is challenging due to the sparse and ambiguous information from the drawn sketches. The current generation models may have difficulty generating detailed texture information. In this work, we propose TexControl, a sketch-based fashion generation framework that uses a two-stage pipeline to generate the fashion image corresponding to the sketch input. First, we adopt ControlNet to generate the fashion image from sketch and keep the image outline stable. Then, we use an image-to-image method to optimize the detailed textures of the generated images and obtain the final results. The evaluation results show that TexControl can generate fashion images with high-quality texture as fine-grained image generation.

翻译：基于深度学习的草图到服装图像生成为时尚设计过程提供了初始设计和灵感。然而，由于手绘草图包含稀疏且模糊的信息，从手绘草图生成服装面临挑战。当前生成模型在生成详细纹理信息时可能存在困难。本文提出了TexControl，一种基于草图的时尚生成框架，采用两阶段流水线生成与输入草图对应的时尚图像。首先，我们采用ControlNet从草图生成时尚图像，并保持图像轮廓稳定。随后，使用图像到图像方法优化生成图像的细节纹理，从而获得最终结果。评估结果表明，TexControl能够生成具有高质量纹理的时尚图像，实现细粒度图像生成。