In recent years, arbitrary image style transfer has attracted more and more attention. Given a pair of content and style images, a stylized one is hoped that retains the content from the former while catching style patterns from the latter. However, it is difficult to simultaneously keep well the trade-off between the content details and the style features. To stylize the image with sufficient style patterns, the content details may be damaged and sometimes the objects of images can not be distinguished clearly. For this reason, we present a new transformer-based method named STT for image style transfer and an edge loss which can enhance the content details apparently to avoid generating blurred results for excessive rendering on style features. Qualitative and quantitative experiments demonstrate that STT achieves comparable performance to state-of-the-art image style transfer methods while alleviating the content leak problem.

本研究介绍了一种新的基于转换器（transformer-based）方法和边缘损失（edge loss）的图像风格转换方法STT，可以在保持较好的风格特征同时提升内容细节，避免产生过度渲染的模糊结果，并解决常见的内容泄漏问题。实验结果表明，STT在图像风格转换方面具有与最先进的方法相当的性能。

基于Transformer的边缘增强图像风格迁移