SAC-Net: Spatial Attenuation Context for Salient Object Detection

by Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Tianyu Wang, and Pheng-Ann Heng.

This implementation is written by Xiaowei Hu at the Chinese University of Hong Kong.

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Citation

@article{hu2020sac,
     author = {Hu, Xiaowei and Fu, Chi-Wing and Zhu, Lei and Wang, Tianyu and Heng, Pheng-Ann},
     title = {SAC-Net: Spatial Attenuation Context for Salient Object Detection},
     journal = {IEEE Transactions on Circuits and Systems for Video Technology},
     year = {2020},
     note = {to appear},
}

Saliency Maps

Please find the predicted saliency maps on the ECSSD, PASCAL-S, SOD, HKU-IS, DUT-OMRON, and DUTS-test at Google Drive.

Installation

1. Please download and compile our CF-Caffe.

2. Put the examples/SAC-Net/ into CF-Caffe/examples/.

Train

Download the ResNet-101 or ResNet-50 model trained on the ImageNet and put this model in CF-Caffe/models/.

1. Enter the ./examples/SAC-Net/SAC-Net-res101/ or ./examples/SAC-Net/SAC-Net-res50/. Modify the image path in train_val.prototxt.

2. Run

   sh train.sh

Test

1. Please download our pretrained model at Google Drive.
   Put this model in ./examples/SAC-Net/SAC-Net-res101/snapshot/.

2. Enter the ./examples/ and run test_saliency.m in Matlab.