Though significant progress has been made in artistic style transfer, semantic information is usually difficult to be preserved in a fine-grained locally consistent manner by most existing methods, especially when multiple artists styles are required to transfer within one single model. To circumvent this issue, we propose a Stroke Control Multi-Artist Style Transfer framework. On the one hand, we develop a multi-condition single-generator structure which first performs multi-artist style transfer. On the one hand, we design an Anisotropic Stroke Module (ASM) which realizes the dynamic adjustment of style-stroke between the non-trivial and the trivial regions. ASM endows the network with the ability of adaptive semantic-consistency among various styles. On the other hand, we present an novel Multi-Scale Projection Discriminator} to realize the texture-level conditional generation. In contrast to the single-scale conditional discriminator, our discriminator is able to capture multi-scale texture clue to effectively distinguish a wide range of artistic styles. Extensive experimental results well demonstrate the feasibility and effectiveness of our approach. Our framework can transform a photograph into different artistic style oil painting via only ONE single model. Furthermore, the results are with distinctive artistic style and retain the anisotropic semantic information.

提出了一种Stroke Control Multi-Artist Style Transfer 框架，为实现多艺术家风格转移设计了多条件单生成器结构和Anisotropic Stroke Module， 并使用 Multi-Scale Projection Discriminator 实现了纹理级别的条件生成， 实验证明了该方法的可行性和有效性。

多画家风格转移的各向异性描边控制