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

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


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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)

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

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