What's the input to the Generator?
In the basic implementation of GANs, the Generator only takes in a vector of random variables. This might seem strange, but after training, the generator can transform this input noise into an image resembling those of the training set.
How does it work?
It is trained along with its counterpart the Discriminator, whose ...
I guess they are talking about adversarial attacks in the same way Szegedy et al. did in "Intriguing properties of neural networks"
They described "adversarial attacks" or "adversarial examples" as images with hardly perceptible perturbations that change the network's prediction.
For example, imagine you've trained a CNN to classify between a variety of ...