CUFD

Code of CUFD: An encoder-decoder network for visible and infrared image fusion based on common and unique feature decomposition

Tips

To train:

• Step1: Download training dataset or create your own training dataset by code.
• Step2: In main.py, keep IS_TRAINING==True and choose the function train_part1.py (the 29th line in main.py), and then run main.py.
• Step3: In main.py, keep IS_TRAINING==True and choose the function train_part2.py (the 31th line in main.py), and then run main.py.

To test with the pre-trained model:

• In main.py, keep IS_TRAINING==False, and run main.py.

If this work is helpful to you, please cite it as:

@article{xu2022cufd,
  title={CUFD: An encoder--decoder network for visible and infrared image fusion based on common and unique feature decomposition},
  author={Xu, Han and Gong, Meiqi and Tian, Xin and Huang, Jun and Ma, Jiayi},
  journal={Computer Vision and Image Understanding},
  pages={103407},
  year={2022},
  publisher={Elsevier}
}

If you have any question, please email to me (meiqigong@whu.edu.cn).