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)

Real-world Smoke dataset can be downloaded here (9xnb)

• 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 junkai.fan@njust.edu.cn.