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BigGAN-Tensorflow

Simple Tensorflow implementation of "Large Scale GAN Training for High Fidelity Natural Image Synthesis" (BigGAN)

main

Issue

The paper used orthogonal initialization, but I used random normal initialization. The reason is, when using the orthogonal initialization, it did not train properly.
I have applied a hierarchical latent space, but not a class embeddedding.

Usage

dataset

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-HQ --gan_type hinge

test

python main.py --phase test --dataset celebA-HQ --gan_type hinge

Architecture

<img src = './assets/architecture.png' width = '600px'>

128x128

<img src = './assets/128.png' width = '600px'>

256x256

<img src = './assets/256.png' width = '600px'>

512x512

<img src = './assets/512.png' width = '600px'>

Author

Junho Kim