Code for "Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection" (AAAI 2020)

conda create -n PCSA python=3.6
conda activate PCSA
conda install pytorch=1.1.0 torchvision -c pytorch
pip install tensorboardX tqdm Pillow==6.2.2
pip install git+https://github.com/pytorch/tnt.git@master
cd Models/PCSA
python setup.py build develop

bash pretrain.sh

bash finetune.sh

The result saliency map and model can be downloaded baidu pan (password t781), or google drive.

For VSOD, we use the evaluation code provided by DAVSOD.

For UVOS, we use the evaluation code provided by Davis16.

python speed.py

If you think this work is helpful, please cite

@inproceedings{gu2020PCSA,
 title={Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection},
 author={Gu, Yuchao and Wang, Lijuan and Wang, Ziqin and Liu, Yun and Cheng, Ming-Ming and Lu, Shao-Ping},
 booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
 year={2020},
}

This project is licensed under the Creative Commons NonCommercial (CC BY-NC 3.0) license where only non-commercial usage is allowed. For commercial usage, please contact us.

The feature extraction backbone is borrowed from d-li14/mobilenetv3.pytorch

Any questions and suggestions, please email ycgu@mail.nankai.edu.cn.