Spider GAN: Leveraging Friendly Neighbors to Accelerate GAN Training
Spider GAN: Leveraging Friendly Neighbors to Accelerate GAN Training
Training Generative adversarial networks (GANs) stably is a challenging task. The generator in GANs transform noise vectors, typically Gaussian distributed, into realistic data such as images. In this paper, we propose a novel approach for training GANs with images as inputs, but without enforcing any pairwise constraints. The intuition is …