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

RANet: Ranking Attention Network for Fast Video Object Segmentation

Ziqin Wang "RANet: Ranking Attention Network for Fast Video Object Segmentation", ICCV 2019, official version, arXiv

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Contact Information

Ziqin Wang

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. (Please download DAVIS 2017 version.)
3. Run RANet.py

Download

Paper

Supplementary File

Precomputed results:Google drive

Pretrained models:Baidu, Google drive

Previous Submission:baidu (code: hoxm), google

Others

Chinese version

Discussion (Chinese)

VOS (Chinese)