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[Accepted by TGRS2022] Official code of the paper "Multi-branch Feature Difference Learning Network for Cross-Spectral Image Patch Matching"

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MFD-Net

!!!Note: The complete training and testing code can be found in ([Link])

  1. We put the trained model weight file on Baidu Netdisk. [link]. Extraction code: jzz6.
  2. Before reproducing the results, you need to download the public VIS-NIR patch dataset by yourself. According to the requirements in the "test.py" file, make them into the corresponding format, and put them in your newly created "data" folder.
  3. Put the model weights file from the link above in your newly created "model" folder. Run "test.py" to reproduce the result (0.88).

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[Accepted by TGRS2022] Official code of the paper "Multi-branch Feature Difference Learning Network for Cross-Spectral Image Patch Matching"

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