论文标题
分辨率依赖于GAN插值，以控制域之间可控图像合成
Resolution Dependent GAN Interpolation for Controllable Image Synthesis Between Domains
论文作者
论文摘要
甘斯可以从训练数据的域中生成照片现实的图像。但是，那些想要将它们用于创造性目的的人通常希望从一个真正的新颖域中产生图像，这是甘恩斯天生无法完成的任务。也希望拥有一定程度的控制水平，以便有一定程度的艺术方向而不是纯粹的随机结果策划。在这里，我们提出了一种以分辨率依赖性方式在StyleGAN架构的生成模型之间进行插值的方法。这使我们能够从一个完全新颖的域中生成图像，并以一定程度的控制输出性质来执行此操作。
GANs can generate photo-realistic images from the domain of their training data. However, those wanting to use them for creative purposes often want to generate imagery from a truly novel domain, a task which GANs are inherently unable to do. It is also desirable to have a level of control so that there is a degree of artistic direction rather than purely curation of random results. Here we present a method for interpolating between generative models of the StyleGAN architecture in a resolution dependent manner. This allows us to generate images from an entirely novel domain and do this with a degree of control over the nature of the output.
