论文标题
针对生成对抗风格转移的域特异性映射
Domain-Specific Mappings for Generative Adversarial Style Transfer
论文作者
论文摘要
样式转移生成了一个图像，其内容来自一个图像和样式。图像到图像的翻译方法具有分离的表示形式，对两个图像类别之间的样式转移有效。但是，以前的方法通常假设共享域不变的内容空间，这可能会损害内容表示功能。为了解决此问题，本文利用特定于域的映射将共享内容空间中的潜在特征重新映射到特定于域的内容空间。这样，可以更正确地编码图像以进行样式传输。实验表明，所提出的方法的表现优于先前的样式转移方法，尤其是在需要图像之间需要语义对应关系的具有挑战性的情况下。代码和结果可在https://acht7111020.github.io/dsmap-demo/上找到。
Style transfer generates an image whose content comes from one image and style from the other. Image-to-image translation approaches with disentangled representations have been shown effective for style transfer between two image categories. However, previous methods often assume a shared domain-invariant content space, which could compromise the content representation power. For addressing this issue, this paper leverages domain-specific mappings for remapping latent features in the shared content space to domain-specific content spaces. This way, images can be encoded more properly for style transfer. Experiments show that the proposed method outperforms previous style transfer methods, particularly on challenging scenarios that would require semantic correspondences between images. Code and results are available at https://acht7111020.github.io/DSMAP-demo/.
