What is: Gradient Normalization?

Gradient Normalization is a normalization method for Generative Adversarial Networks to tackle the training instability of generative adversarial networks caused by the sharp gradient space. Unlike existing work such as gradient penalty and spectral normalization, the proposed GN only imposes a hard 1-Lipschitz constraint on the discriminator function, which increases the capacity of the network.