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deep-learningdcgan

How discriminator works on DCGAN?

I studying about DCGAN, and I wonder something about it.

In Ian Goodfellow's natural GAN, discriminator Model outputs one scalar value what means the probability. But DCGAN's discriminator has designed with CNN architecture. I know that CNN's output is vector of class probabilities.

So how discriminator works on DCGAN? And what output of DCGAN's discriminator is?

Solution

  • See Image Completion with Deep Learning in TensorFlow for a long answer.

    In short: Suppose you make a CNN which has n filters of the size of its input and valid-padding. Then the output will be of shape n x 1 x 1. Then you can apply softmax to that shape and you have the probabilities in the channels.

    You might also want to read 2.2.1. Convolutional Layers of my Masters thesis.