Skip to content

Latest commit

 

History

History
68 lines (44 loc) · 2.4 KB

README.md

File metadata and controls

68 lines (44 loc) · 2.4 KB
Raw

Contour Knowledge Transfer for Salient Object Detection

by Xin Li, Fan Yang, Hong Cheng, Wei Liu and Dinggang Shen

Introduction

This repository is for 'Contour Knowledge Transfer for Salient ObjectDetection'.

Installation

For installation, please follow the instructions of Caffe.

The code has been tested successfully on Ubuntu 14.04 with CUDA 8.0.

Usage

  1. Clone the repository:

    git clone https://github.com/lixin666/C2SNet.git

  2. Build Caffe and pycaffe:

    cd caffe-master
cp Makefile.config.example Makefile.config
vim Makefile.config
make -j8 && make pycaffe

ps: You should uncomment 'WITH_PYTHON_LAYER := 1' in Makefile.config before compiling.

  1. Test:

    • Test code is in folder 'code'.

    • We provide two models trained with 10K (MSRA10K) and 30K (MSRA10K + Web Images) training images. Download trained models and put them in folder 'code/models':

    • C2SNet10K.caffemodel: BaiduYun or GoogleDrive

    • C2SNet30K.caffemodel: BaiduYun or GoogleDrive

    • Put the test images in folder 'images', and run

    python run_demo.py

    -After that, the results will be genrated in folder 'res'.

  2. Results:

Citation

If C2SNet is useful for your research, please consider citing:

@inproceedings{xin2018c2s,
  author = {Li, Xin and Yang, Fan and  Cheng, Hong, and Liu, Wei and Shen, Dinggang},
  title = {Contour Knowledge Transfer for Salient Object Detection},
  booktitle = {ECCV},
  year = {2018}
}

Question

Please contact 'xinli_uestc@hotmail.com' Or 'fanyang_uestc@hotmail.com'