Neural saliency algorithm guide bi‐directional visual perception style transfer

Abstract

The artistic style transfer of images aims to synthesise novel images by combining the content of one image with the style of another, which is a long-standing research topic and already has been widely applied in real world. However, defining the aesthetic perception from the human visual system is a challenging problem. In this study, the authors propose a novel method for automatic visual perception style transfer. First, they render a novel saliency detection algorithm to automatically perceive the visual attention of an image. Then, different from conventional style transfer algorithm in which style transferring is applied uniformly across all image regions, the authors apply a saliency algorithm to guide the style transferring process, enabling different types of style transferring to occur in different regions. Extensive experiments show that the proposed saliency detection algorithm and the style transfer algorithm are superior in performance and efficiency.