Reviews: Improved Precision and Recall Metric for Assessing Generative Models

Originality: This paper uses similar intuition as [1]. Precision should represent the generated images captured by real images and the recall should represent the real images should be captured by generated images. Instead of using PR curve, the authors use two values definition as information retrieval metric and claim it is better by showing counterexample in StyleGAN with truncation trick. I think the main contribution is the empirical evaluations on large-scale GANs. They evaluated StyleGAN and BigGAN and show the tradeoff between precision and recall by controlling the truncation trick.