A Gentle Introduction to the Progressive Growing GAN

Progressive Growing GAN is an extension to the GAN training process that allows for the stable training of generator models that can output large high-quality images.

It involves starting with a very small image and incrementally adding blocks of layers that increase the output size of the generator model and the input size of the discriminator model until the desired image size is achieved.

This approach has proven effective at generating high-quality synthetic faces that are startlingly realistic.

In this post, you will discover the progressive growing generative adversarial network for generating large images.

After reading this post, you will know:

• GANs are effective at generating sharp images, although they are limited to small image sizes because of model stability.
• Progressive growing GAN is a stable approach to training GAN models to generate large high-quality images that involves incrementally increasing the size of the model during training.
• Progressive growing GAN models are capable of generating photorealistic synthetic faces and objects at high resolution that are remarkably realistic.

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