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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This package contains the source code which is associated with the following paper: Huafeng Li, Yueliang Cen, Yu Liu, Xun Chen, Zhengtao Yu, "Different Input Resolutions and Arbitrary Output Resolution: A Meta-Learning Based Deep Framework for Infrared and Visible Image Fusion", IEEE Transactions on Image Processing, vol. 30, pp. 4070-4083, 2021. Edited by Yueliang Cen and Yu Liu. Usage of this code is free for research purposes only. Please refer to the above publication if you use this code. Thank you. Thank you. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Requirements: CUDA 10 Python 3.7 Pytorch 1.3.1 torchvision 0.4 numpy 1.17 cv2 4.1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Install and run demo: 1. download the code git clone https://github.com/yuliu316316/MetaLearning-Fusion.git cd MetaLearning-Fusion 2. run the demo file: python demo.py 3. Train: 3.1. Train the whole network: python main.py 3.2. And then fine-turn the fusion branch with the contrast loss: python main.py --finetune_AAF %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Contact: Don't hesitate to contact me if you meet any problems when using this code. Yu Liu Department of Biomedical Engineering Hefei University of Technology Email: yuliu@hfut.edu.cn; lyuxxz@163.com Homepage: https://sites.google.com/site/yuliu316316; https://github.com/yuliu316316 Last update: 27-July-2022
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