Simple Tensorflow implementation of RelativisticGAN
- For 256x256, the network does not generate the image properly. (DCGAN Architecture)
- I think,
RaDRAGANmore better thanRaLSGAN
> python download.py celebAmnistandcifar10are used inside keras- For
your dataset, put images like this:
├── dataset
└── YOUR_DATASET_NAME
├── xxx.jpg (name, format doesn't matter)
├── yyy.png
└── ...
- python main.py --phase train --dataset celebA --Ra True --gan_type dragan
- python main.py --phase test --dataset celebA --Ra True --gan_type dragan
"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
| Name | Formulation |
|---|---|
| GAN |  |
| RGAN |  |
| RaGAN |  |
| RaGAN-GP |  |
| RaLSGAN |  |
| RaHingeGAN |  |
- 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.
| Name | Original | Original + Ra |
|---|---|---|
| GAN |  |
 |
| LSGAN |  |
 |
| DRAGAN |  |
 |
- In the case of
DRAGAN, the images are sometimes distorted during the training
Junho Kim