The evaluation of Generative Adversarial Networks (GANs) is a very active and exciting research field in generative models for generative models. Evaluation is the procedure through which we estimate the quality of our model and the samples produced with it. In this chapter, you will learn how to use different methods to evaluate the quality and variety of the GAN samples you produced in Chapter 3, Implementing your First GAN.
You will learn about the challenges involved in evaluating GAN samples. You will understand and learn to implement metrics for image quality. You will learn about using the birthday paradox to evaluate sample variety.
The following topics will be covered in this chapter:
- The evaluation of GANs
- Qualitative methods
- Quantitative methods
- GANs and the birthday paradox