The code of "CAMF: An Interpretable Infrared and Visible Image Fusion Network Based on Class Activation Mapping"
tensorflow-gpu 1.15
opencv-python
Pillow
scipy 1.2.1
Download the pre-trained checkpoint from here and put them in ./checkpoint/
Run python test_one_image.py
to test. The test_dataset can be set as 'tno', 'roadscene' or 'medical'.
The auto-encoder is trained using the MS-COCO dataset.
You can download my training set from here or download the original data from the official website.
Run python train_auto_encoder.py
to train the auto-encoder network.
Run python train_classifier.py
to train the classifier network.
@article{tang2023camf,
title={CAMF: An Interpretable Infrared and Visible Image Fusion Network Based on Class Activation Mapping},
author={Tang, Linfeng and Chen, Ziang and Huang, Jun and Ma, Jiayi},
journal={IEEE Transactions on Multimedia},
year={2023},
publisher={IEEE}
}