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This is the official PyTorch implementation of our TIP 2021paper.
git clone https://github.com/zal0302/CII.gitcd CII/Download the followingdatasets for testing and unzip them intodata folder.
Download the following pre-trained models for CII withResNet50 backbone andResNet18 backbone intosaved/models folder.
For all datasets testing used in our paper for ResNet50 backbone:
python test.py -r saved/models/cii.pth -c saved/models/config.json
and for ResNet18 backbone:
python test.py -r saved/models/cii_res18.pth -c saved/models/config_resnet18.json
All results saliency maps will be stored undersaved/results folders in .png formats.
You may refer to this repo for results evaluation:SalMetric.
We provide the pre-computed saliency maps and evaluation results forResNet50 backbone andResNet18 backbone.
If you have any questions, feel free to contact me via:liuzhiang(at)mail.nankai.edu.cn.
@article{liu2021rethinking, title={Rethinking the U-Shape Structure for Salient Object Detection}, author={Liu, Jiang-Jiang and Liu, Zhi-Ang and Peng, Pai and Cheng, Ming-Ming}, journal={IEEE Transactions on Image Processing}, volume={30}, pages={9030--9042}, year={2021}, publisher={IEEE}}@article{liu2022poolnet+, title={Poolnet+: Exploring the potential of pooling for salient object detection}, author={Liu, Jiang-Jiang and Hou, Qibin and Liu, Zhi-Ang and Cheng, Ming-Ming}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, year={2022}, publisher={IEEE}}