Awesome
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 result saliency map and model can be downloaded baidu pan (password t781), or google drive.
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},
}
License
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.
Related Project
The feature extraction backbone is borrowed from d-li14/mobilenetv3.pytorch
Contact
Any questions and suggestions, please email ycgu@mail.nankai.edu.cn.