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 thanRaLSGAN
Usage
dataset
> python download.py celebA
mnist
andcifar10
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.
Name | Original | Original + Ra |
---|---|---|
GAN | ![]() |
![]() |
LSGAN | |
|
HingeGAN | Will be soon | |
DRAGAN | |
|
Error
Original DRAGAN
- In the case of
DRAGAN
, the images are sometimes distorted during the training
Author
Junho Kim