CrossFuse: A Novel Cross Attention Mechanism based Infrared and Visible Image Fusion Approach

Accetped by Information Fusion 103(2024) 102147, https://doi.org/10.1016/j.inffus.2023.102147
Hui Li*, Xiao-Jun Wu
paper, Arxiv

Platform

Python 3.7
Pytorch >= 1.8

Training Dataset

KAIST (S. Hwang, J. Park, N. Kim, Y. Choi, I. So Kweon, Multispectral pedestrian detection: Benchmark dataset and baseline, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 1037–1045.) is utilized to train LRRNet.

CrossFuse - Fusion framework

Cross Attention Mechanism

If you have any question about this code, feel free to reach me([email protected], [email protected])

Citation

@article{li2024crossfuse,
  title={{CrossFuse: A Novel Cross Attention Mechanism based Infrared and Visible Image Fusion Approach}},
  author={Li, Hui and Wu, Xiao-Jun},
  journal={Information Fusion},
  volume={103},
  pages={102147},
  year={2024},
  publisher={Elsevier}
}