A Gentle Introduction to StyleGAN the Style Generative Adversarial Network

Taken from: A Style-Based Generator Architecture for Generative Adversarial Networks. We can review each of these changes in more detail. The StyleGAN generator and discriminator models are trained using the progressive growing GAN training method. This means that both models start with small images, in this case, 4 4 images. The models are fit until stable, then both discriminator and generator are expanded to double the width and height (quadruple the area), e.g. 8 8. A new block is added to each model to support the larger image size, which is faded in slowly over training. Once faded-in, the models are again trained until reasonably stable and the process is repeated with ever-larger image sizes until the desired target image size is met, such as 1024 1024.