Official PyTorch implementation of Defocus and Similarity Attention Fusion Net (DSAF-Net), which is an end-to-end network to merge information from several multi-focus and misaligned images in the focal stack to obtain a clear and detailed image.

• Download the repository: git clone https://github.com/PeimingCHEN/DSAF-Net.
  
• Install Python 3.7.10, Pytorch 1.8.1, and CUDA 11.1.
• Install the dependencies: pip install -r requirement.txt.
  

You can find the WHU-MFM dataset here. Please upload the training set to the dataset/ folder and the testing set to the test/ folder. Each sample consists of a focal stack with 5 images. We adopt the 480 × 360 version of WHU-MFM and shuffle it in the unit of the focal stack to train and test DSAF-Net.

• To train the Defocus-Net: python train.py.
  
• To train the OpticalFlow-Net: python train_raft.py.
  
• To joint training and test the Fusion-Net: python train_fusion.py.
  A single GPU is enough to carry out it.
  

More fusion results on WHU-MFM testing dataset are shown in the results/ folder.