【论文】Neural Style Transfer综述(附相关论文的代码和预训练模型下载链接)

论文《Neural Style Transfer: A Review》主要是对Neural Style Transfer的相关文章做了一个综述，在同样条件下对一些算法做了比较，并给出了综述中所涉及论文的代码以及预训练模型下载链接。

摘要：

The recent work of Gatys et al. demonstrated the power of Convolutional Neural Networks (CNN) in creating artistic fantastic imagery by separating and recombing the image content and style. This process of using CNN to migrate the semantic content of one image to different styles is referred to as Neural Style Transfer. Since then, Neural Style Transfer has become a trending topic both in academic literature and industrial applications. It is receiving increasing attention from computer vision researchers and several methods are proposed to either improve or extend the original neural algorithm proposed by Gatys et al. However, there is no comprehensive survey presenting and summarizing recent Neural Style Transfer literature. This review aims to provide an overview of the current progress towards Neural Style Transfer, as well as discussing its various applications and open problems for future research.

论文链接：

https://arxiv.org/abs/1705.04058

代码及预训练模型链接：

https://github.com/ycjing/Neural-Style-Transfer-Papers

原文链接：

http://weibo.com/5023909156/F2LVABFDH?type=comment#_rnd1494576480388