Backseason DFI Save

Dynamic Feature Integration for Simultaneous Detection of Salient Object, Edge and Skeleton

This is a demo PyTorch implementation of our IEEE TIP 2020 paper.

We also provide an Online Demo.

Prerequisites

• Pytorch 0.4.1+
• torchvision
• opencv

Demo usage

1. Clone the repository

git clone https://github.com/backseason/DFI.git
cd DFI/

2. Download the pretrained model

dfi.pth GoogleDrive | BaiduYun (pwd: wkeb) and move it to the pretrained folder.

3. Test (demo)

The source images are in the demo/images folder. By running

python main.py

you'll get the predictions under the demo/predictions folder. The predictions of all the three tasks are performed simultaneously.

4. Pre-computed results and evaluation results

You can find the pre-computed predictions maps of all the three tasks and their corresponding evaluation scores with the following link: Results reported in the paper GoogleDrive | BaiduYun (pwd: 7eg3)

5. Contact

If you have any questions, feel free to contact me via: j04.liu(at)gmail.com.

If you think this work is helpful, please cite

@article{liu2020dynamic,
  title={Dynamic Feature Integration for Simultaneous Detection of Salient Object, Edge and Skeleton},
  author={Jiang-Jiang Liu and Qibin Hou and Ming-Ming Cheng},
  journal={IEEE Transactions on Image Processing},
  year={2020},
  volume={},
  number={},
  pages={1-15},
  doi={10.1109/TIP.2020.3017352},
}