Image Generation Using GANs
In the previous chapter, we learned about manipulating an image using neural style transfer and super-imposed the expression in one image on another. However, what if we give the network a bunch of images and ask it to come up with an entirely new image, all on its own?
Generative adversarial networks (GANs) are a step toward achieving the feat of generating an image given a collection of images. In this chapter, we will start by learning about the idea behind what makes GANs work, before building one from scratch. This is a vast field that is expanding even as we write this book. This chapter will lay the foundation of GANs by covering three variants; we will learn about more advanced GANs and their applications in the next chapter.
In this chapter, we will explore the following topics:
- Introducing GANs
- Using GANs to generate handwritten digits
- Using DCGANs to generate face images
- Implementing conditional GANs
