- Spectral Normalization is the current state-of-the-art method for enforcing the Lipschitz constraint on the discriminator of the GAN. I was interested specially in the sensitivity of the discriminator to minor changes in the image input to it. While stability to small changes in the image is a desirable property of the discriminator, it’s not satisfied by the discriminator and some interesting trends are observed.
- Contribution:
- Detection & analysis of the problems with Spectral Normalized GANs & attempts to improve them to produce meaningful & coherent generations.
- Designed a method to quantitatively estimate local and global coherence captured by the discriminator.
- Github link
