论文标题
Adawct：自适应美白和着色样式注射
AdaWCT: Adaptive Whitening and Coloring Style Injection
论文作者
论文摘要
自适应实例归一化（ADAIN）已成为样式注入的标准方法：通过通过缩放和迁移操作重新划算功能，它发现在样式传输，图像生成和图像到图像到图像转换中广泛使用。在这项工作中，我们提出了Adain的概括，该概括依赖于我们配音的美白和着色转化（WCT），我们将其申请在大型gan中申请样式注入。我们通过对Starganv2体系结构的实验来表明，这种概括在概念上很简单，从而显着改善了生成的图像的质量。
Adaptive instance normalization (AdaIN) has become the standard method for style injection: by re-normalizing features through scale-and-shift operations, it has found widespread use in style transfer, image generation, and image-to-image translation. In this work, we present a generalization of AdaIN which relies on the whitening and coloring transformation (WCT) which we dub AdaWCT, that we apply for style injection in large GANs. We show, through experiments on the StarGANv2 architecture, that this generalization, albeit conceptually simple, results in significant improvements in the quality of the generated images.
