BEGAN: Boundary Equilibrium Generative Adversarial Networks

31 Mar 2017 David Berthelot Thomas Schumm Luke Metz

We propose a new equilibrium enforcing method paired with a loss derived from the Wasserstein distance for training auto-encoder based Generative Adversarial Networks. This method balances the generator and discriminator during training... (read more)

PDF Abstract

Results from the Paper


Ranked #30 on Image Generation on CIFAR-10 (Inception score metric)

     Get a GitHub badge
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Image Generation CIFAR-10 BEGAN Inception score 5.62 # 30

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet