Skip to content

JoshuaEbenezer/cwgan

master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

CWGAN

Conditional Wasserstein Generative Adversarial Network for image-to-image translation.

Implementation of the paper: Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks.

Please cite the following work if you use this code:

Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks J.P. Ebenezer, B. Das, S. Mukhopadhyay 2019 27th European Signal Processing Conference (EUSIPCO), 1-5

Arxiv link: https://arxiv.org/pdf/1903.00395.pdf

Training a model

  1. Clone/download the repo
  2. Go to ./scripts/
  3. Change the database location and the other options in train_pix2pix.sh and execute it.

Testing a model

  1. After training the model, go to ./scripts/
  2. Change the database location and the other options in test_pix2pix.sh and execute it.

Acknowledgements

This code is based on https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix (for cGAN) and https://github.com/caogang/wgan-gp (for wGAN).

About

Conditional Wasserstein Generative Adversarial Network for image-to-image translation.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published