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Towards High-Resolution Salient Object Detection

Introduction

This package contains the source code for Towards High-Resolution Salient Object Detection, ICCV2019.

Datasets

HRSOD [Google Drive] [Baidu Yun](For the link of Baidu Yun, images of HRSOD-Training are splited into two parts just because of single file size limitation.)
DAVIS-S Download

Pre-computed Saliency Maps

Saliency maps of this paper along with compared state-of-the-art methods can be can be downloaded
HRSOD
DAVIS-S

More saliency maps of this paper on widely used benchmarks can be downloaded
THUR
HKU-IS
DUTS-Test
PASCAL-S
DUT-OMRON
ECSSD
HRSOD
DAVIS-S

Source Code

Usage

  1. Download our code into your computer

  2. Cd to HRSOD-master/caffe-master, follow the official instructions to build caffe. The code has been tested successfully on Ubuntu 14.04 with CUDA 8.0.

  3. Make caffe & matcaffe

     make all -j  
     make matcaffe -j  
    
  4. Download pretrained caffemodel from baidu yun and put the file under the root directory HRSOD-master/.

  5. Change parameters in init_iccv19_demo.m and then run test_iccv19_demo.m to get the saliency maps. The results will be saved in HRSOD-master/results/.

Citation

If you find our works useful in your research, please consider citing:

@InProceedings{Zeng_2019_ICCV,
  author = {Zeng, Yi and Zhang, Pingping and Zhang, Jianming and Lin, Zhe and Lu, Huchuan},
  title = {Towards High-Resolution Salient Object Detection},
  booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
  month = {October},
  year = {2019}
}

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  • Jupyter Notebook 57.7%
  • C++ 33.4%
  • Python 3.9%
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