Awesome

All-In-One-Underwater-Image-Enhancement-using-Domain-Adversarial-Learning

Code for All-In-One Underwater Image Enhancement using Domain-Adversarial Learning [paper] [arXiv]

Synthesized NYU Depth V2 Underwater Dataset based on Anwar et al. (2018)

All the dependencies can be installed by creating a conda environment from the environment.yml file as follows

conda env create --name envname -f=environments.yml

Some parts of code adopted from https://github.com/milesial/Pytorch-UNet and https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix

If you find this work helpful and plan to use this in your project, please cite us by using the following bibtex

@InProceedings{Uplavikar_2019_CVPR_Workshops,
author = {M Uplavikar, Pritish and Wu, Zhenyu and Wang, Zhangyang},
title = {All-in-One Underwater Image Enhancement Using Domain-Adversarial Learning},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}