A Review on Neural Style Transfer
Jiayue Li, Qing Wang, Hong Chen, Jiahui An, Shiji Li · Journal of Physics Conference Series · 2020
Abstract Image style transfer is a method that can output styled images, which can both retain the original image content and add new artistic style. When using neural network, this method is referred as Neural Style Transfer (NST), which is a hot topic in the field of image processing and video processing. This article will provide a comprehensive overview of the current NST methods. Firstly, we introduce the current progress of NST from two aspects: the image-optimisation-based method and model-optimisation-based method. Then we compare and summarize different types of the NST algorithms. The review concludes with a discussion of applications of NST and some proposals for future research.