DiffAugment
DiffAugment
**Differentiable Augmentation (DiffAugment)** is a set of differentiable image transformations used to augment data during [GAN](https://paperswithcode.com/method/gan) training. The transformations are applied to the real and generated images. It enables the gradients to be propagated through the augmentation back to the generator, regularizes
the discriminator without manipulating the target distribution, and maintains the balance of training
dynamics. Three choices of transformation are preferred by the authors in their experiments: Translation, [CutOut](https://paperswithcode.com/method/cutout), and Color.
Differentiable Augmentation for Data-Efficient GAN Training
https://paperswithcode.com/paper/differentiable-augmentation-for-data
Differentiable Augmentation for Data-Efficient GAN Training