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SN-GAN

PyTorch implementation of Spectral Normalization for Generative Adversarial Networks

Prerequistes

Usage

  • Clone this repo:
git clone https://github.com/godisboy/SN-GAN.git
cd SN-GAN
  • Train the standard model for 32*32 image size
python train.py --cuda(optional) 
  • Train the Res-Generator and Res-Discriminator for 64*64 image size
python train-res.py --cuda --dataPath /Path/to/yourdataset/

  1. Result of SN-GAN on CIFAR10 dataset
  • Generated

Generated samples

  • Generated

Generated samples

  • Generated samples with Standard Generator and ResDiscriminator

Generated samples

Note: The ResBlock of Res-Generator is different from what implemented in original paper. This repo use UpsamplingBilinear instead of Uppooling for Upsampling operation.

To Do

Acknowledgments

Based on the implementation DCGAN and official implementation with Chainer sngan_projection

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