You can find the orginal PReMVOS paper and code here
It has a good performance on video object segmentation, better fits the large-scale video segmentation and achieved an accuracy of 69%, ranked 9th in the The 2nd Large-scale Video Object Segmentation Challenge Workshop in conjunction with ICCV2019, Seoul, Korea
It could be also used in medical area like MRI Segmentaion, and has a satifying performance when segmentation the different tissue in human brain.
If you use this code, please consider citing the following papers:
@inproceedings{luiten2018premvos,
title={PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation},
author={Jonathon Luiten and Paul Voigtlaender and Bastian Leibe},
booktitle={Asian Conference on Computer Vision},
year={2018}
}
@article{Luiten18CVPRW,
author = {Jonathon Luiten and Paul Voigtlaender and Bastian Leibe},
title = {{PReMVOS: Proposal-generation, Refinement and Merging for the DAVIS Challenge on Video Object Segmentation 2018}},
journal = {The 2018 DAVIS Challenge on Video Object Segmentation - CVPR Workshops},
year = {2018}
}
@article{Luiten18ECCVW,
author = {Jonathon Luiten and Paul Voigtlaender and Bastian Leibe},
title = {{PReMVOS: Proposal-generation, Refinement and Merging for the YouTube-VOS Challenge on Video Object Segmentation 2018}},
journal = {The 1st Large-scale Video Object Segmentation Challenge - ECCV Workshops},
year = {2018}
}