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Towards Good Practices for Video Object Segmentation

2019-09-30 11:00:09
Dongdong Yu, Kai Su, Hengkai Guo, Jian Wang, Kaihui Zhou, Yuanyuan Huang, Minghui Dong, Jie Shao, Changhu Wang
arXiv_CV
     
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.

Abstract (translated)

URL

https://arxiv.org/abs/1909.13583

PDF

https://arxiv.org/pdf/1909.13583.pdf

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