UNFusion: A unified multi-scale densely connected network for infrared and visible image fusion

Zhishe Wang, Junyao Wang, Yuanyuan Wu, Jiawei Xu, Xiaoqin Zhang

paper

Platform

Python 3.7
Pytorch >=1.6.0

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 auto-encoder network.

Tips:

Large files should be downloaded separately, including the following files:

For testing:

• trained model
  Extraction code: mv8n

Citation

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

@ARTICLE{9528393,
  author={Wang, Zhishe and Wang, Junyao and Wu, Yuanyuan and Xu, Jiawei and Zhang, Xiaoqin},
  journal={IEEE Transactions on Circuits and Systems for Video Technology}, 
  title={UNFusion: A unified multi-scale densely connected network for infrared and visible image fusion}, 
  year={2021},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TCSVT.2021.3109895}}

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