Junkai Fan, Fei Guo, Xiang Li, Jianjun Qian, Jun li* and Jian Yang*
(* indicates the corresponding author)
PCA Lab, Nanjing University of Science and Technology;
- [18-08-2024] We have released the PhoneHazy dataset (real-world hazy scenarios).
Overall pipeline of our non-aligned supervision framework with physical priors for the real-world image dehazing. It includes the mvSA and non-aligned supervision modules. mvSA can effectively estimate the infinite airlight A∞ in real scenes. Our framework is different from the supervised dehazing models as it does not require aligned ground truths.
Our phone-hazy dataset contains 415 non-aligned image pairs with four primary scenes: buildings, urban highways, rural cement roads, and outdoor landscapes. The haze levels mainly vary within a visibility range of 0 to 50 meters.
PhoneHazy dataset can be downloaded here (quf8)
- Ubuntu 18.04
- Python == 3.9
- PyTorch == 1.11 with CUDA 11.3
- torchvision ==0.12.0
- numpy == 1.22.3
If you are interested in this work, please consider citing:
@article{fan2023non,
title={Non-aligned supervision for Real Image Dehazing},
author={Fan, Junkai and Guo, Fei and Qian, Jianjun and Li, Xiang and Li, Jun and Yang, Jian},
journal={arXiv preprint arXiv:2303.04940},
year={2023}
}
@inproceedings{fan2024driving,
title={Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistance},
author={Fan, Junkai and Weng, Jiangwei and Wang, Kun and Yang, Yijun and Qian, Jianjun and Li, Jun and Yang, Jian},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={26109--26119},
year={2024}
}This code is based on the CycleGAN. Thank them for their outstanding work.
If you have any question or suggestion, please contact [email protected].