soprof/RelativisticGAN-Tensorflow

Simple Tensorflow implementation of RelativisticGAN

RelativisticGAN-Tensorflow

Simple Tensorflow implementation of RelativisticGAN

Issue

• For 256x256, the network does not generate the image properly. (DCGAN Architecture)
• I think, RaDRAGAN more better than RaLSGAN

Usage

dataset

> python download.py celebA

• mnist and cifar10 are used inside keras
• For your dataset, put images like this:

├── dataset
   └── YOUR_DATASET_NAME
       ├── xxx.jpg (name, format doesn't matter)
       ├── yyy.png
       └── ...

train

• python main.py --phase train --dataset celebA --Ra True --gan_type dragan

test

• python main.py --phase test --dataset celebA --Ra True --gan_type dragan

Summary

"the discriminator estimates the probability that the given real data is more realistic than a randomly sampled fake data"

= RGAN

"the discriminator estimates the probability that the given real data is more realistic than fake data, on average"

= RaGAN

Idea

Formulation

Name	Formulation
GAN
RGAN
RaGAN
RaGAN-GP
RaLSGAN
RaHingeGAN

Results

• 128x128 celebA
• 200k iterations (but, 100k iteration is also enough)
• RaDRAGAN is not in the paper, I just tried because I wanted to do it.
• 256x256 celebA is being training, but quality is not good...

RaGAN

RaLSGAN

RaDRAGAN

RaHingeGAN (in training)

Author

Junho Kim