C2RF
(IJCV 2025) Official Pytorch implementation of "C2RF: Bridging Multi-modal Image Registration and Fusion via Commonality Mining and Contrastive Learning"
Install / Use
/learn @QinglongYan-hub/C2RFREADME
C2RF
This is official Pytorch implementation of "C2RF: Bridging Multi-modal Image Registration and Fusion via Commonality Mining and Contrastive Learning". Please click here to download this paper.
1. Recommended Environment
- [ ] torch 1.10.2+cu102
- [ ] torchvision 0.8.2
- [ ] kornia 0.5.2
2. Framework
The framework of the proposed C2RF for multi-modal image registration and fusion.

3. Pretrained Weights
Please download the pretrained weights at the link below, and then place them into the folder ./checkpoint/
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The pretrained weights for the Roadscene dataset is at Google Drive.
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The pretrained weights for the PET-MRI dataset is at Google Drive.
4. To Test
Registration and Fusion
RoadScene dataset
python test.py --dataset=RoadScene
PET-MRI dataset
python test.py --dataset=PET-MRI
5. To Train
Training the fusion model
RoadScene dataset
python train_Fu.py --dataset=RoadScene
PET-MRI dataset
python train_Fu.py --dataset=PET-MRI
Training the registration model
RoadScene dataset
python train_Reg.py --dataset=RoadScene
PET-MRI dataset
python train_Reg.py --dataset=PET-MRI
