39 lines
995 B
Markdown
39 lines
995 B
Markdown
# PFCFuse: A Poolformer and CNN fusion network for Infrared-Visible Image Fusion
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The implementation of our paper "PFCFuse: A Poolformer and CNN fusion network for Infrared-Visible Image Fusion".
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## Recommended Environment:
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python=3.8\
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torch=1.12.1+cu113\
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scipy=1.9.3\
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scikit-image=0.19.2\
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scikit-learn=1.1.3\
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tqdm=4.62.0
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## Network Architecture:
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Our PFCFuse is implemented in ``net.py``.
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## Training:
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### Data preprocessing
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Run
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```
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python dataprocessing.py
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```
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### Model training
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Run
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```
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python train.py
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```
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## Testing:
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Run
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```
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python test_IVF.py
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```
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## 相关工作
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```
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@inproceedings{zhao2023cddfuse,
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title={Cddfuse: Correlation-driven dual-branch feature decomposition for multi-modality image fusion},
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author={Zhao, Zixiang and Bai, Haowen and Zhang, Jiangshe and Zhang, Yulun and Xu, Shuang and Lin, Zudi and Timofte, Radu and Van Gool, Luc},
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booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
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pages={5906--5916},
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year={2023}
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}
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```
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