Awesome
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
Network architecture
Information flow diagrams
Dependencies
- python 3.6.9
- tensorflow-gpu (1.14.0)
- numpy (1.14.0)
- Pillow (5.0.0)
- scikit-image (0.13.0)
- scipy (1.0.1)
- matplotlib (2.0.0)
Resources
- Pretrained models: MNIST, MNIST_multi, GTA<->BDD, CelebA, VGG19
- Training & Testing data in tf-record format: MNIST, MNIST_multi. GTA<->BDD, CelebA. Note: For the GTA<->BDD experiment, the data are prepared with RGB images of 512x1024 resolution, and segmentation labels of 8 categories. They are provided used for further research. In our paper, we use RGB images of 256x512 resolution without and segmentation labels.
- Segmentation model Refer to DeepLab-ResNet-TensorFlow
TF-record data preparation steps (Optional)
You can skip this data preparation procedure if directly using the tf-record data files.
cd datasets./run_convert_mnist.shto download and convert mnist and mnist_multi to tf-record format../run_convert_gta_bdd.shto 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.shto convert the images to tf-record format. You can directly download the prepared data or download and process data from CelebA website .
Training steps
- Replace the links
data,logs,weightswith your own directories or links. - Download VGG19 into 'weights' directory.
- Download the tf-record training data to the
data_parent_dir(default./data). - Modify the
data_parent_dir,checkpoint_dirand comment/uncomment the target experiment in therun_train_feaMask.shandrun_train_EGSCIT.shscripts. - Run
run_train_feaMask.shto pretrain the feature mask network. Then runrun_train_EGSCIT.sh.
Testing steps
- Replace the links
data,logs,weightswith your own directories or links. - (Optional) Download the pretrained models to the
checkpoint_dir(default./logs). - Download the tf-record testing data to the
data_parent_dir(default./data). - Modify the
data_parent_dir,checkpoint_dirand comment/uncomment the target experiment in therun_test_EGSCIT.shscript. - run
run_test_EGSCIT.sh.
Citation
@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}
}