EGNet:Edge Guidance Network for Salient Object Detection (ICCV 2019)

1. Clone this code by git clone https://github.com/JXingZhao/EGNet.git --recursive, assume your source code directory is$EGNet;

2. Download training data (fsex);

3. Download initial model (8ir7);

4. Change the image path and intial model path in run.py and dataset.py;

5. Start to train with python3 run.py --mode train.

1. Download pretrained model (2cf5);

2. Change the test image path in dataset.py

3. Generate saliency maps for SOD dataset by python3 run.py --mode test --sal_mode s, PASCALS by python3 run.py --mode test --sal_mode p and so on;

| Page | | Training Set (fsex) | | Pretrained models (2cf5) | | Saliency maps (54gi) |

@inproceedings{zhao2019EGNet,
 title={EGNet:Edge Guidance Network for Salient Object Detection},
 author={Zhao, Jiaxing and Liu, Jiangjiang and Fan, Dengping and Cao, Yang and Yang, Jufeng and Cheng, Ming-Ming},
 booktitle={The IEEE International Conference on Computer Vision (ICCV)},
 month={Oct},
 year={2019},
}