Image Style Transfer in Deep Learning Networks

被引:0
|
作者
Li, Yuanhao [1 ]
Zhang, Tianying [1 ]
Han, Xu [1 ]
Qi, Yali [1 ]
机构
[1] Beijing Inst Graph Commun, Sch Informat Engn, Beijing, Peoples R China
关键词
CNN; Neural Style Transfer; deep learning;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Since Gatys et al. proved that the convolution neural network(CNN) can be used to generate new images with artistic styles by separating and recombining the styles and contents of images. Neural Style Transfer has attracted wide attention of computer vision researchers. This paper aims to provide an overview of the style transfer application deep learning network development process, and introduces the classical style migration model, on the basis of the research on the migration of style of the deep learning network for collecting and organizing, and put forward related to gathered during the investigation of the problem solution, finally some classical model in the image style to display and compare the results of migration.
引用
收藏
页码:660 / 664
页数:5
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