Summary

In this chapter, we have explored 3D-GANs. We started with an introduction to a 3D-GAN and covered the architecture and the configurations of the generator and the discriminator. Then, we went through the different steps required to set up a project. We also looked at how to prepare the dataset. Finally, we implemented a 3D-GAN in the Keras framework and trained it on our dataset. We also explored different hyperparameter options. We concluded the chapter by exploring the practical applications of 3D-GANs.

In the next chapter, we will learn how to perform face aging using Conditional Generative Adversarial Networks (cGANs).