PyramidCSA

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

Build

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

Training

pretrain phase

bash pretrain.sh

finetune phase

bash finetune.sh

Results

The trained model, and result saliency map can be downloaded here (password t781).

Evaluation

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

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

Speed Evaluation

python speed.py

Cite

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},
}

Related Project

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

Concat

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

qsharpsword/PyramidCSA