Improving Arbitrary Style Transfer with Transformer-based Style Consistency and Contrastive Learning

The proposed method utilizes a novel Style Consistency Instance Normalization (SCIN) to align content and style features, and an Instance-based Contrastive Learning (ICL) approach to enhance the quality of stylized images by learning stylization-to-stylization relations.