Flow Adaptive Video Object Segmentation

作者：

Highlights：

• We introduce a deep learning based approach with a novel online adaptation technique using optical flow.

• We achieve state-of-the-art results on the DAVIS Challenges with considerably lower model complexity.

• We introduce an interactive user interface for the model to achieve production-level accuracy.

摘要

•We introduce a deep learning based approach with a novel online adaptation technique using optical flow.•We achieve state-of-the-art results on the DAVIS Challenges with considerably lower model complexity.•We introduce an interactive user interface for the model to achieve production-level accuracy.

论文关键词：Video object segmentation,Optical flow,Online adaptation,Semi-supervised,Interactive,Object tracking

论文评审过程：Received 29 September 2019, Revised 4 December 2019, Accepted 5 December 2019, Available online 21 December 2019, Version of Record 3 January 2020.

论文官网地址：https://doi.org/10.1016/j.imavis.2019.103864