Towards Good Practices for Video Object Segmentation

Dongdong Yu, Kai Su, Hengkai Guo, Jian Wang, Kaihui Zhou, Yuanyuan Huang, Minghui Dong, Jie Shao, Changhu Wang; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 0-0

Abstract


Semi-supervised video object segmentation is an interesting yet challenging task in machine learning. In this work, we conduct a series of refinements with the propagation-based video object segmentation method and empirically evaluate their impact on the final model performance through ablation study. By taking all the refinements, we improve the space-time memory networks to achieve a Overall of 79.1 on the Youtube-VOS Challenge 2019.

Related Material


[pdf]
[bibtex]
@InProceedings{Yu_2019_ICCV,
author = {Yu, Dongdong and Su, Kai and Guo, Hengkai and Wang, Jian and Zhou, Kaihui and Huang, Yuanyuan and Dong, Minghui and Shao, Jie and Wang, Changhu},
title = {Towards Good Practices for Video Object Segmentation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}