How to train the discriminator network?

[hailuoS]

In this paper, the discriminator network takes a probability map of size H × W × C and outputs a confidence map of size H × W × 1. I don't understand how to train this discriminator network, what are the labels during the training phase ? As my understanding, when the probability map comes from the ground truth, the label is a map of size H × W × 1 and the values in the map are all 1, in contrast, when the probability map comes from the segmentation network, the label is a map of size H × W × 1 and the values in the map are all 0. Am I right? Hope to get your answer. Thanks so much

[hfslyc]

Yes, you are right. It's like training a GAN with spatial ground truths. Please refer to https://github.com/hfslyc/AdvSemiSeg/blob/master/train.py#L380-L412 for how to train the discriminator network.