Guided Video Object Segmentation by Tracking

The paper presents Guided video object segmentation by tracking (gVOST) method for a human -in-the-loop video object segmentation which significantly reduces the manual annotation effort. The method is designed for an interactive object segmentation in a wide range of videos with a minimal user input. User to iteratively selects and annotates a small set of anchor frames by just a few clicks on the object border. The segmentation then is propagated to intermediate frames. Experiments show that gVOST performs well on diverse and challenging videos used in visual object tracking (VOT2020 dataset) where it achieves an IoU of 73% at only 5% of the user annotated frames. This shortens the annotation time by 98% compared to the brute force approach. gVOST outperforms the state-of-the-art interactive video object segmentation methods on the VOT2020 dataset and performs comparably on a less diverse DAVIS video object segmentation dataset.