MMGAN: Manifold Matching Generative Adversarial Network

Understand

It is well-known that GANs are difficult to train, and several different techniques have been proposed in order to stabilize their training.

• In this paper, we propose a novel training method called manifold-matching, and a new GAN model called manifold-matching GAN (MMGAN).
• MMGAN finds two manifolds representing the vector representations of real and fake images.
• If these two manifolds match, it means that real and fake images are statistically identical.