C2RF

This is official Pytorch implementation of "C2RF: Bridging Multi-modal Image Registration and Fusion via Commonality Mining and Contrastive Learning (IJCV 2025)"

@article{Tang2024C2RF,
	title={C2RF: Bridging Multi-modal Image Registration and Fusion via Commonality Mining and Contrastive Learning}, 
	author={Tang, Linfeng and Yan, Qinglong and Xiang, Xinyu and Fang, Leyuan and Ma, Jiayi},
	journal={International Journal of Computer Vision}, 
	year={2025},
}

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/

• The pretrained weights for the Roadscene dataset is at Google Drive.

• 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