Coarse-to-Fine Structure-Aware Artistic Style Transfer

Author:

Liu Kunxiao,Yuan GuowuORCID,Wu Hao,Qian Wenhua

Abstract

Artistic style transfer aims to use a style image and a content image to synthesize a target image that retains the same artistic expression as the style image while preserving the basic content of the content image. Many recently proposed style transfer methods have a common problem; that is, they simply transfer the texture and color of the style image to the global structure of the content image. As a result, the content image has a local structure that is not similar to the local structure of the style image. In this paper, we present an effective method that can be used to transfer style patterns while fusing the local style structure to the local content structure. In our method, different levels of coarse stylized features are first reconstructed at low resolution using a coarse network, in which style color distribution is roughly transferred, and the content structure is combined with the style structure. Then, the reconstructed features and the content features are adopted to synthesize high-quality structure-aware stylized images with high resolution using a fine network with three structural selective fusion (SSF) modules. The effectiveness of our method is demonstrated through the generation of appealing high-quality stylization results and a comparison with some state-of-the-art style transfer methods.

Funder

Natural Science Foundation of China

Application and Foundation Project of Yunnan Province

Department of Science and Technology of Yunnan Province–Yunnan University Joint Special Project for Double-Class Construction

Expert Workstation of Yunnan Province

Postgraduate Practice and Innovation Project of Yunnan University

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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