AEFusion: A multi-scale fusion network combining Axial attention and Entropy feature Aggregation for infrared and visible images

Bicao Li, Jiaxi Lu, Zhoufeng Liu, Zhuhong Shao, Chunlei Li, Yifan Du, Jie Huang

paper

Platform

Python =3.6
Pytorch =1.5.0
scipy =1.2.0

Training Dataset

MS-COCO 2014 (T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, and C. L. Zitnick. Microsoft coco: Common objects in context. In ECCV, 2014. 3-5.) is utilized to train our network.

Train and Test

train_network.py
test.py

Tips:

The evaluation metrics in the paper can be found here.

Citation

@article{LI2023109857,
author = {Bicao Li, Jiaxi Lu, Zhoufeng Liu, Zhuhong Shao, Chunlei Li, Yifan Du and Jie Huang},
title = {AEFusion: A multi-scale fusion network combining Axial attention and Entropy feature Aggregation for infrared and visible images},
journal = {Applied Soft Computing},
volume = {132},
pages = {109857},
year = {2023},
issn = {1568-4946},
doi = {https://doi.org/10.1016/j.asoc.2022.109857},
url = {https://www.sciencedirect.com/science/article/pii/S1568494622009061}

If you have any question, please email to us (lbc@zut.edu.cn or lujiaxi@zut.edu.cn).