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SMoA: Searching a Modality-Oriented Architecture for Infrared and Visible Image Fusion

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Introduction

This is the implementation of the paper SMoA: Searching a Modality-Oriented Architecture for Infrared and Visible Image Fusion.

Requirements

  • python >= 3.6
  • pytorch == 1.7
  • torchvision == 0.8

Datasets

You can download the datasets here.

Test

python test.py

Train from scratch

step 1

python train_search.py

step 2

Find the string which descripting the searched architectures in the log file. Copy and paste it into the genotypes.py, the format should consist with the primary architecture string.

step 3

python train.py

Citation

If you use any part of this code in your research, please cite our paper:

@ARTICLE{9528046,
author={Liu, Jinyuan and Wu, Yuhui and Huang, Zhanbo and Liu, Risheng and Fan, Xin},
journal={IEEE Signal Processing Letters},
title={SMoA: Searching a Modality-Oriented Architecture for Infrared and Visible Image Fusion},
year={2021},
volume={28},
number={},
pages={1818-1822},
doi={10.1109/LSP.2021.3109818}}

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