/RANet

RANet: Ranking Attention Network for Fast Video Object Segmentation (VOS), ICCV2019

Primary LanguagePythonApache License 2.0Apache-2.0

Ziqin Wang, Jun Xu, Li Liu, Fan Zhu, Ling Shao, "RANet: Ranking Attention Network for Fast Video Object Segmentation", ICCV 2019, official version, arXiv

Contact Information

Ziqin Wang

For academic

wangziqin@stu.xjtu.edu.cn

ziqin.wang.edu@gmail.com

ziqin.wang@outlook.com


Contents

  1. Introduction
  2. Code
  3. Download
  4. Others
  5. Citation

Introduction

1. Overview

2. Framework

3. Ranking

Code

1. Requirement

Pytorch (tested on 1.0.1 and 0.4.1)

torchvision = 0.2

2. Usage

  1. Download the pretained model from this page.
  2. Link DAVIS folder into datasets folder.
  3. Run RANet.py

Download

Paper

Supplementary File

Precomputed results:Google drive

Pretrained models:Baidu, Google drive

Others

Chinese version

Discussion (Chinese)

VOS (Chinese)

Citation:

@InProceedings{Ziqin2019RANet,
               author = {Wang, Ziqin and Xu, Jun and Liu, Li and Zhu, Fan and Shao, Ling},
               title = {RANet: Ranking Attention Network for Fast Video Object Segmentation},
               booktitle={2019 IEEE/CVF International Conference on Computer Vision (ICCV)}, 
               year = {2019}
	   pages={3977-3986}
               }