论文标题
素描到艺术：合成草图的风格化艺术图像
Sketch-to-Art: Synthesizing Stylized Art Images From Sketches
论文作者
论文摘要
我们提出了一种新的方法，用于合成草图中详细详细的艺术风格图像。给定草图，没有语义标记，并且是特定样式的参考图像，该模型可以通过颜色和纹理合成有意义的细节。该模型由三个明确设计的模块组成，用于更好的艺术风格捕获和发电。基于GAN框架，引入了双掩蔽机制来强制（从草图）强制执行内容约束，并开发了特征图转换技术来增强样式一致性（到参考图像）。最后，提出了实例归一化的逆过程，以解散样式和内容信息，因此可以产生更好的综合性能。实验证明了基于先前最新的技术对基准的显着定性和定量提升，该技术是针对拟议过程所采用的。
We propose a new approach for synthesizing fully detailed art-stylized images from sketches. Given a sketch, with no semantic tagging, and a reference image of a specific style, the model can synthesize meaningful details with colors and textures. The model consists of three modules designed explicitly for better artistic style capturing and generation. Based on a GAN framework, a dual-masked mechanism is introduced to enforce the content constraints (from the sketch), and a feature-map transformation technique is developed to strengthen the style consistency (to the reference image). Finally, an inverse procedure of instance-normalization is proposed to disentangle the style and content information, therefore yields better synthesis performance. Experiments demonstrate a significant qualitative and quantitative boost over baselines based on previous state-of-the-art techniques, adopted for the proposed process.
