# FusionDN

**Repository Path**: wdwdwd123/FusionDN

## Basic Information

- **Project Name**: FusionDN
- **Description**: Code of FusionDN (AAAI 2020): A Unified Densely Connected Network for Image Fusion
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-10-06
- **Last Updated**: 2021-10-06

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# FusionDN<br>
This is the code of the following paper (tensorflow):<br>
```
@inproceedings{xu2020aaai,
  title={FusionDN: A Unified Densely Connected Network for Image Fusion},
  author={Xu, Han and Ma, Jiayi and Le, Zhuliang and Jiang, Junjun and Guo, Xiaojie},
  booktitle={Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI)},
  pages={12484--12491},
  year={2020}
}
```


It is a unified model for multiple image fusion tasks, including:<br>
1) visible and infrared image fusion<br>
2) multi-exposure image fusion<br>
3) multi-focus image fusion<br>


## Framework:<br>
 Overall procedure:<br>
<div align=center><img src="https://github.com/hanna-xu/FusionDN/blob/master/imgs/procedure.jpg" width="440" height="290"/></div><br>

Intuitive description of data flow and the process of EWC:<br>
<div align=center><img src="https://github.com/hanna-xu/FusionDN/blob/master/imgs/MultiTask.jpg" width="510" height="200"/></div><br>

## Fused results:<br>
<div align=center><img src="https://github.com/hanna-xu/FusionDN/blob/master/imgs/res1.jpg" width="900" height="490"/></div>
<div align=center><img src="https://github.com/hanna-xu/FusionDN/blob/master/imgs/res2.jpg" width="900" height="400"/></div>

## To train:<br>
CUDA_VISIBLE_DEVICES=0,1 python main.py (2 GPUs are needed)<br><br>

## To test:<br>
CUDA_VISIBLE_DEVICES=0 python test_main.py<br><br>

## Tips:<br>
Large files should be downloaded separately, including the following files: <br>
#### For training:<br>
* [Training dataset](https://pan.baidu.com/s/18hQyGNlhVb3oXAXOJ5LZCQ)<br>
The code to create your own training dataset can be found [*here*](https://github.com/hanna-xu/utils).
* [vgg16](https://pan.baidu.com/s/1vK3l8rzgAkxcKpLvnFAwXA) (put it in 'VGGnet/')<br>

#### For testing:<br>
* [Trained model](https://pan.baidu.com/s/1zH6DC0N78Mw2jvPRB2I6HA)<br>

If you have any question, please email to me (xu_han@whu.edu.cn).