Training data for video segmentation are expensive to annotate. This impedes extensions of
end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary …

Zero-shot video object segmentation (ZS-VOS) aims to segment foreground objects in a
video sequence without prior knowledge of these objects. However, existing ZS-VOS …

Existing approaches to unsupervised video instance segmentation typically rely on motion
estimates and experience difficulties tracking small or divergent motions. We present …

Video object segmentation (VOS) plays an important role in video analysis and
understanding, which in turn facilitates a number of diverse applications, including video …

Semi-supervised video object segmentation is the task of segmenting the target in
sequential frames given the ground truth mask in the first frame. The modern approaches …

Unsupervised video object segmentation has made significant progress in recent years, but
the manual annotation of video mask datasets is expensive and limits the diversity of …

Unsupervised video object segmentation (UVOS) aims at detecting the primary objects in a
given video sequence without any human interposing. Most existing methods rely on two …

Video segmentation encompasses a wide range of categories of problem formulation, eg,
object, scene, actor-action and multimodal video segmentation, for delineating task-specific …

In this paper, we present a two-stage unsupervised foreground object segmentation network
tailored for dynamic scenes affected by atmospheric turbulence. In the first stage, we utilize …

The objective of this paper is motion segmentation--discovering and segmenting the moving
objects in a video. This is a much studied area with numerous careful, and sometimes …