In this chapter, we have learned about leveraging two different neural networks to generate new images of handwritten digits using GANs. Next, we generated realistic faces using DCGANs. Finally, we learned about conditional GANs, which help us in generating images of a certain class. Having generated images using different techniques, we could still see that the generated images were not sufficiently realistic. Furthermore, while we generated images by specifying the class of images we want to generate in conditional GANs, we are still not in a position to perform image translation, where we ask to replace one object in the image with another one, with everything else left as is. In addition, we are yet to have an image generation mechanism where the number of classes (styles) to generate is more unsupervised.
In the next chapter, we will learn about generating images that are more realistic using some of the latest variants of GANs. In addition, we will learn about generating...
