Fig. 2

Overview over one training epoch. In (a) the critic function is trained. A t1 image is passed through the generator. The generator’s output is a map which gets added to the t1 image. This produces the fake t2 image. The real and the fake t2 images are then passed to the critic. The output of the critic is incorporated into a loss function and backpropagated to update the weights of the critic network. In (b) the generator is trained. Again, a t1 image is passed to the generator. The output is added to the t1 image to create the fake t2 image. This is passed to the critic. The output is incorporated into the generator loss function and backpropagated through both networks to update the generator network