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MEF-GAN

This is the code for "multi-exposure image fusion via generative adversarial networks".

Architecture:<br>

<div align=center><img src="https://github.com/hanna-xu/MEF-GAN/blob/master/imgs/Architecture.png" width="740" height="320"/></div><br>

Fused results:<br>

<div align=center><img src="https://github.com/hanna-xu/MEF-GAN/blob/master/imgs/results.png" width="700" height="390"/></div>

To train:<br>

CUDA_VISIBLE_DEVICES=0,1 python main.py <br> (2 GPUs are needed. One is for the self-attention block and the other one is for other blocks and the discriminator.)<br>

To test:<br>

CUDA_VISIBLE_DEVICES=0,1 python test_main.py<br>

Tips:<br>

The training dataset is too large to be uploaded and downloaded. It may be more convenient to create your own dataset. <br> The multi-exposure image pairs can be downloaded here. <br> The code to create your own training dataset can be found here.<br> (size_input=144. The channel dimension: 1:3 over-exposed patches, 4:6 under-exposed patches, 7:9 ground-truth patches.)

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