Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Last update: Dec 14, 2022

Related tags

Deep Learning HMMN

Overview

Hierarchical Memory Matching Network for Video Object Segmentation

Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

ICCV 2021

This is the implementation of HMMN.
This code is based on STM (ICCV 2019): [link].
Please see our paper for the details: [paper]

Dependencies

Python 3.8
PyTorch 1.8.1
numpy, opencv, pillow

Trained model

Download pre-trained weights into the same folder with demo scripts
Link: [weights]

Code

DAVIS-2016 validation set (Single-object)

python eval_DAVIS.py -g '0' -s val -y 16 -D [path/to/DAVIS]

DAVIS-2017 validation set (Multi-object)

python eval_DAVIS.py -g '0' -s val -y 17 -D [path/to/DAVIS]

Pre-computed Results

We also provide pre-computed results for benchmark sets.

Bibtex

@inproceedings{seong2021hierarchical,
  title={Hierarchical Memory Matching Network for Video Object Segmentation},
  author={Seong, Hongje and Oh, Seoung Wug and Lee, Joon-Young and Lee, Seongwon and Lee, Suhyeon and Kim, Euntai},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  year={2021}
}

Terms of Use

This software is for non-commercial use only. The source code is released under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) Licence (see this for details)

Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Related tags

Overview

Hierarchical Memory Matching Network for Video Object Segmentation

Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

ICCV 2021

Dependencies

Trained model

Code

Pre-computed Results

Bibtex

Terms of Use

Owner

Hongje Seong

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