- This is the sample code of saliency detection for 2017 cvpr paper [Instance-Level Salient Object Segmentation] by Guanbin Li, Yuan Xie, Liang Lin and Yizhou Yu
- This code is tested on MATLAB 2014b on Ubuntu14.04
- For more information, please visit our project page (http://hcp.sysu.edu.cn/instance-level-salient-object-segmentation)
This code includes
- 'deeplab-caffe': the Caffe toolbox for Multiscale Refinement Network (MSRNet)
- 'models_prototxts': pre-trained models and prototxts
- 'code': codes to do testing
- 'data':
- a.imgs: source images to do saliency detection
- b.pre: predicted results
Please follow the instructions below to run the code.
- Compile the
Caffe
andmatcaffe
in thedeeplab-caffe
package. - Put your own images in the
data/imgs
directory - Download the pretrained MSRNet-VGG models by running the script
./models_prototxts/get_msrnet-vgg_model.sh
- Generate saliency map by running the matlab code
./code/demo.m
If you find this useful, please cite our work as follows:
@inproceedings{MSRNet2017object,
title={Instance-Level Salient Object Segmentation},
author={Guanbin Li, Yuan Xie, Liang Lin and Yizhou Yu},
booktitle={CVPR},
year={2017}
}
Please contact "xiey39@mail2.sysu.edu.cn" if any questions with the code.