sungonce / hmmn

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

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.

• [DAVIS-16-val]
• [DAVIS-17-val]
• [DAVIS-17-test-dev]
• [YouTube-VOS-18-valid]
• [YouTube-VOS-19-valid]

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)