[hjk05]

I feel like the reporting on these things using just the generated images is completely off point. Showing an image of a face and saying: “can you believe this is fake isn’t it amazing?” Just has me going meh? At the very minimum show the “completely fake” generated image next to the closest image from the training sets used. Otherwise how do I know you haven’t just built an over-engineered solution that picks a random number between 0 and the number of images you had available for training?

[astazangasta]

The nature of the Generator is that it is seeded with random inputs and trains so it is able to fool the adversarial classifier. I.e. it never sees the "true" data.

[rytill]

This isn’t completely accurate. The generator sees the training data in the same way supervised learning might, because the discriminator sees the data, and the generator shares gradients with the discriminator.

Your point stands though, that it’s obviously not overfitting, and no scientist would publish a result that was just overfitting face generation.