We address the problem of semi-supervised video object segmentation (VOS), where the masks of objects of interests are given in the first frame of an input video. To deal with challenging cases where objects are occluded or missing, previous work …
This paper presents a class-agnostic video object segmentation approach that won the 3rd place in the 2018 DAVIS Challenge (semi-supervised track). The proposed approach does not use any semantic object re-identification module and thus is more …