Chapter 7: High Fidelity Face Generation
As GANs began to become more stable to train, thanks to improvements to loss functions and normalization techniques, people started to shift their focus to trying to generate higher-resolution images. Previously, most GANs were only capable of generating images up to a resolution of 256x256, and simply adding more upscaling layers to the generator did not help.
In this chapter, we will look at techniques that are capable of generating images of high resolutions of 1024x1024 and beyond. We will start by implementing a seminal GAN known as Progressive GAN, sometimes abbreviated to ProGAN. This was the first GAN that was successful at generating 1024x1024 high-fidelity face portraits. High-fidelity doesn't just mean high-resolution but also a high resemblance to a real face. We can have a high-resolution generated face image, but if it has four eyes, then it isn't high fidelity.
After ProGAN, we will implement StyleGAN, which...
