Abstract. We propose a new framework for estimating generative models via adversarial nets, in which we simultaneously train two models: a generative model G ...

We propose a new framework for estimating generative models via an adversar- ial process, in which we simultaneously train two models: a generative model G.

Jun 10, 2014 · Abstract:We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two ...

Our results on various datasets demonstrate that Triple-GAN as a unified model can simultaneously (1) achieve the state-of-the-art classification results among ...

Training generative adversarial networks (GAN) using too little data typically leads to discriminator overfitting, causing training to diverge.

Duration: 1:55:54
Posted: Jan 18, 2018

Mar 20, 2017 · by Li Yang Ku (gooly) Generating realistic images with machines was always one of the top items on my list of difficult tasks.