2021
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds
NeurIPS 2021poster
Conditional GANs (cGAN), in their rudimentary form, suffer from critical drawbacks such as the lack of diversity in generated outputs and distortion between the latent and output manifolds. Although efforts have been made to improve results, they can suffer from unpleasant side-effects such as the…