Tensorflow implementation of ICLR2019 paper "Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency"
Tensorflow implementation of ICLR 2019 paper Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency
You can skip this data preparation procedure if directly using the tf-record data files.
cd datasets
./run_convert_mnist.sh
to download and convert mnist and mnist_multi to tf-record format../run_convert_gta_bdd.sh
to convert the images and segmentation to tf-record format. You need to download data from GTA5 website and BDD website. Note: this script will reuse gta data downloaded and processed in ./run_convert_gta_bdd.sh
./run_convert_celeba.sh
to convert the images to tf-record format. You can directly download the prepared data or download and process data from CelebA website .data
, logs
, weights
with your own directories or links.data_parent_dir
(default ./data
).data_parent_dir
, checkpoint_dir
and comment/uncomment the target experiment in the run_train_feaMask.sh
and run_train_EGSCIT.sh
scripts.run_train_feaMask.sh
to pretrain the feature mask network. Then run run_train_EGSCIT.sh
.data
, logs
, weights
with your own directories or links.checkpoint_dir
(default ./logs
).data_parent_dir
(default ./data
).data_parent_dir
, checkpoint_dir
and comment/uncomment the target experiment in the run_test_EGSCIT.sh
script.run_test_EGSCIT.sh
.@article{ma2018exemplar,
title={Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency},
author={Ma, Liqian and Jia, Xu and Georgoulis, Stamatios and Tuytelaars, Tinne and Van Gool, Luc},
journal={ICLR},
year={2019}
}