TransGAN: Two Transformers Can Make One Strong GAN
Code used for TransGAN: Two Transformers Can Make One Strong GAN.
News
checkpoint for generating images on celeba64 dataset is released!
Main Pipeline
Visual Results
prepare fid statistic file
mkdir fid_stat
Download the pre-calculated statistics
(Google Drive) to ./fid_stat
.
Environment
pip install -r requirements.txt
Notice: Pytorch version has to be <=1.3.0 !
Training
Coming soon
Testing
Firstly download the checkpoint from (Google Drive) to ./pretrained_weight
# cifar-10
sh exps/cifar10_test.sh
# stl-10
sh exps/stl10_test.sh
# celeba64
sh exps/celeba64_test.sh
Acknowledgement
Codebase from AutoGAN, pytorch-image-models
Citation
if you find this repo is helpful, please cite
@article{jiang2021transgan,
title={TransGAN: Two Transformers Can Make One Strong GAN},
author={Jiang, Yifan and Chang, Shiyu and Wang, Zhangyang},
journal={arXiv preprint arXiv:2102.07074},
year={2021}
}