Studies Advanced in Image Style Transfer based on Deep Learning

Abstract

Image style transfer (IST) is a hot topic in the computer vision community, which refers to learning the distribution of a given style image to convert any image into corresponding image style while the content of the original image is preserved as much as possible. Early style transfer mainly utilizes texture features. Thanks to the great improvement of deep learning technology, researches on IST based on convolutional neural networks (CNN) have achieved breakthroughs in accuracy and speed. Focusing on the topic of deep learning-based IST, we will introduce the latest algorithms in detail, including their basic ideas, key steps, advantages, and disadvantages. Also, we will give an analysis of the performance of representative methods. Furthermore, we discuss the problems to be solved in style transfer and summarize the challenges and development trends in the future.