Update README.md

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Zhaozixiang1228 2023-05-19 14:46:15 +02:00
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@ -3,9 +3,9 @@ Codes for ***CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for M
[Zixiang Zhao](https://zhaozixiang1228.github.io/), [Haowen Bai](), [Jiangshe Zhang](http://gr.xjtu.edu.cn/web/jszhang), [Yulun Zhang](https://yulunzhang.com/), [Shuang Xu](https://shuangxu96.github.io/), [Zudi Lin](https://zudi-lin.github.io/), [Radu Timofte](https://www.informatik.uni-wuerzburg.de/computervision/home/) and [Luc Van Gool](https://vision.ee.ethz.ch/people-details.OTAyMzM=.TGlzdC8zMjQ4LC0xOTcxNDY1MTc4.html).
-[*[Paper]*]()
-[*[Paper]*](https://openaccess.thecvf.com/content/CVPR2023/html/Zhao_CDDFuse_Correlation-Driven_Dual-Branch_Feature_Decomposition_for_Multi-Modality_Image_Fusion_CVPR_2023_paper.html)
-[*[ArXiv]*](https://arxiv.org/abs/2104.06977)
-[*[Supplementary Materials]*]()
-[*[Supplementary Materials]*](https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhao_CDDFuse_Correlation-Driven_Dual-Branch_CVPR_2023_supplemental.pdf)
## Update
@ -16,13 +16,13 @@ Codes for ***CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for M
## Citation
```
@article{CDDFuse,
author = {Zixiang Zhao and Haowen Bai and Jiangshe Zhang and Yulun Zhang and Shuang Xu and Zudi Lin and Radu Timofte and Luc Van Gool},
title = {CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {},
year = {2023},
pages = {}
@InProceedings{Zhao_2023_CVPR,
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},
title = {CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
pages = {5906-5916}
}
```
@ -65,7 +65,7 @@ CDDFuse 7.44 54.67 16.36 2.3 1.81 0.69 0.52 0.98
```
which can match the results in Table 1 in our original paper.
The output for ``'test_IVF.py'`` is:
The output for ``'test_MIF.py'`` is:
```
================================================================================