BAUST-Net: Balance-Aware Universal Image Style Transfer

The current style transfer methods usually suffer from an imbalance in learning the content features and style features. Some of them tend to learn style information in the style domain, while others are more affinitive with the content domain. This feature imbalance learning leads to unsatisfactory image visual performance and thus provides a new perspective for the image style transfer study. In this work, we propose a novel Balance-Aware Universal Image Style Transfer Network (BAUST-Net) to p