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Code for the paper

Code for the paper in CVPR2019, 'Multi-source weak supervision for saliency detection' (download the pdf file)

Results

score/datasetsECSSDHKU-ISPASCALSSODOMRONDUTS-testSED1SED2
max$F_\beta$.878.856.790.799.718.767.902.849
MAE.096.084.134.167.114.096.081.097

Download result maps: OneDrive / GoogleDrive

Usage

Test

  1. Environment: python2.7, pytorch'1.0'

  2. Download models and put in the current folder

  3. Run

python main.py \
--img_dir 'path/to/images(.jpg)' \
--gt_dir 'path/to/ground-truth(.png)'

Train

Please checkout the other branch of this repo

Citation

@inproceedings{zeng2019multi,
  title={Multi-source weak supervision for saliency detection},
  author={Zeng, Yu and Zhuge, Yunzhi and Lu, Huchuan and Zhang, Lihe and Qian, Mingyang and Yu, Yizhou},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
  year={2019}
}