Advanced GANs to Manipulate Images
In the previous chapter, we learned about leveraging Generative Adversarial Networks (GANs) to generate realistic images. In this chapter, we will learn about leveraging GANs to manipulate images. We will learn about two variations of generating images using GANs – paired and unpaired methods. With the paired method, we will provide the input and output pair combinations to generate novel images based on an input image, which we will learn about in the Pix2Pix GAN. With the unpaired method, we will specify the input and output; however, we will not provide one-to-one correspondence between the input and output, but expect the GAN to learn the structure of the two classes, and convert an image from one class to another, which we will learn about when we discuss CycleGAN.
Another class of unpaired image manipulation involves generating images from a latent space of random vectors and seeing how images change as the latent vector values change...
