U-Net GAN
U-Net Generative Adversarial Network
In contrast to typical GANs, a U-Net GAN uses a segmentation network as the discriminator. This segmentation network predicts two classes: real and fake. In doing so, the discriminator gives the generator region-specific feedback. This discriminator design also enables a  [CutMix](https://paperswithcode.com/method/cutmix)-based consistency regularization on the two-dimensional output of the U-Net GAN discriminator, which further improves image synthesis quality.
A U-Net Based Discriminator for Generative Adversarial Networks
https://paperswithcode.com/paper/a-u-net-based-discriminator-for-generative-1
A U-Net Based Discriminator for Generative Adversarial Networks