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CVPR2020 Memory aggregation networks for efficient interactive video object segmentation

This is the pytorch implementation of the CVPR2020 paper "Memory aggregation networks for efficient interactive video object segmentation".

Preparation

Dependencies

• Python 3.7
• Pytorch 1.0
• Numpy
• tensorboardX
• davisinteractive (Please refer to this link)

Pretrained model

Download deeplabV3+ model pretrained on COCO to this repo.

Dataset

Download DAVIS2017 and scribbles into one folder. Please refer to DAVIS.

If you need the file "DAVIS2017/ImageSets/2017/v_a_l_instances.txt", please refer to the link https://drive.google.com/file/d/1aLPaQ_5lyAi3Lk3d2fOc_xewSrfcrQlc/view?usp=sharing

Train and Test

sh run_local.sh

Evaluation

You can download our model and decompress it for evaluation.

Citation

Please cite this paper in your publications if it helps your research:

@inproceedings{miao2020memory,
  title={Memory aggregation networks for efficient interactive video object segmentation},
  author={Miao, Jiaxu and Wei, Yunchao and Yang, Yi},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={10366--10375},
  year={2020}
}