A Review on Neural Style Transfer

Jiayue Li, Qing Wang, Hong Chen, Jiahui An, Shiji Li

Research output: Contribution to journalConference articlepeer-review

8 Scopus citations

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.

Original languageEnglish
Article number012156
JournalJournal of Physics: Conference Series
Volume1651
Issue number1
DOIs
StatePublished - 25 Nov 2020
Externally publishedYes
Event2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020 - Guilin, China
Duration: 21 Aug 202023 Aug 2020

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