基于深度学习的图像风格迁移研究综述

图像风格迁移是一种用不同风格渲染图像语义内容的图像处理方法。随着深度学习的兴起，图像风格迁移获得了进一步的发展，并取得了一系列突破性的研究成果。其出色的风格迁移能力引起了学术界和工业界的广泛关注，具有重要的研究价值。为推进基于深度学习的图像风格迁移的技术研究，本文对目前的主要方法和代表性工作进行了归纳与探讨。首先回顾了非参数的图像风格迁移，详细介绍了目前主要的基于深度学习的图像风格迁移的基本原理和方法，分析了图像风格迁移在相关领域中的应用前景，最后总结了基于深度学习的图像风格迁移目前存在的问题与未来的研究方向。

A Survey of Image Style Transfer Based on Deep Learning

Image style transfer is an image processing method that renders the semantic content of an image in different styles. With the rise of deep learning, image style transfer has gained further development and has achieved a series of breakthrough research results. Its outstanding style transfer ability has attracted wide attention from academic and industrial circles and has important research value. In order to promote the technology research of image style transfer based on deep learning, this paper summarizes and discusses the current major methods and representative work. Firstly, this paper reviews the non-parametric image style transfer, and introduces the basic principles and methods of image style transfer based on deep learning, and analyzes the application prospect of image style transfer technology in related fields. At last, this paper summarizes the existing problems and future research directions of image style transfer based on deep learning.