I Introduction
Image style transfer is an important subject in the field of image processing, and the important task is to transfer the style of one image to the other. Before the rise of neural networks, rendering various styles in images is difficult. For the traditional algorithms, due to lack of explicit semantic information for image representation, it is not possible to separate images from styles. Deep learning can adaptively extract features from the training data, and it has certain inherent advantages to deal with the problem which is difficult to model. In recent years, with the development of big data algorithms and the improvement of computer power, deep learning techniques have shown more powerful effects than other traditional techniques in the fields of image recognition, segmentation, and composition.