[UPDATE!] Our paper just gets accepted by RA-L! Thanks to reviewers, collaborators, editors, and those who raise issues on GitHub which helped us improve the code a lot.
All data presented in the paper are now released.\ Example: Download 'data_lego_white' and put it under the neuralsea directory. Download white lego weights and put it under neuralsea/checkpoints/ to use our pretrained weights (not all weights are released so far. I will upload them once I got time. Feel free to train from scratch and I don't usually stick with certain random seeds.).
Our paper is published at IEEE RA-L. You can also find it on arxiv. To appear on ICRA 2024.\ This work is supported by National Oceanic and Atmospheric Administration (NOAA) under grant NA22OAR0110624.
Left: with water effects; Right: color corrected \ \ Groundtruth image\
\ Groundtruth image\
More real-world results:\ Lake Erie:\ \ \ Water Tank Low Turbidity:\ \ Water Tank Mid Turbidity:\ \ Water Tank High Turbidity:\
Install PyTorch:
pip install torch torchvision
Install PyTorch3D, please follow their instruction. We use the following to install:
pip install "git+https://github.com/facebookresearch/pytorch3d.git"
Install other dependencies:
pip install hydra-core plotly visdom matplotlib
# for synthetic data example
python3 train_nerf.py --config-name synthetic_lego_white
python3 test_nerf.py --config-name synthetic_lego_white
# for water tank data example
python3 train_nerf.py --config-name real_watertank
python3 test_nerf.py --config-name real_watertank
install visdom
pip install visdom
run visdom
visdom
Then in your browser, navigate to http://localhost:8097/
If you find this study helpful please kindly cite us:
@ARTICLE{10225666,
author={Zhang, Tianyi and Johnson-Roberson, Matthew},
journal={IEEE Robotics and Automation Letters},
title={Beyond NeRF Underwater: Learning Neural Reflectance Fields for True Color Correction of Marine Imagery},
year={2023},
volume={8},
number={10},
pages={6467-6474},
doi={10.1109/LRA.2023.3307287}}
(Irrelavant to this paper) Our field work featured on noaa.gov