让风格图像的局部结构融入内容图像，生成更自然的艺术化作品。
Coarse-to-Fine Structure-Aware Artistic Style Transfer
- 分粗细两阶段：先低分辨率融合风格与内容结构，再高分辨率精细重建。
- 通过三模块结构选择性融合，使风格局部特征与内容结构对齐。
- 适合追求艺术风格与内容一致性、避免错位失真的用户。
艺术风格迁移旨在将风格图像的艺术表现力保留的同时，融合内容图像的基本结构，生成目标图像。现有方法普遍存在仅将风格图像的纹理与色彩整体转移到内容图像全局结构的问题，导致局部结构不匹配。本文提出一种有效方法，在保持内容结构的基础上，融合风格图像的局部结构特征。首先，通过粗网络在低分辨率下重建多层级的风格特征，初步实现风格色彩分布转移，并融合内容与风格结构。随后，利用细网络结合重构特征与内容特征，通过三个结构选择性融合（SSF）模块，生成高质量的结构感知式高分辨率风格化图像。实验表明，该方法在生成效果和与前沿方法的对比中均表现优异。
原文摘要 · Abstract (English)
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 into the local content structure. In our method, dif-ferent 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 com-parison with some state-of-the-art style transfer methods.
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