This paper studies the problem of semi-supervised video object segmentation (VOS).
Multiple works have shown that memory-based approaches can be effective for video object …

In this paper, we propose a novel solution for object-matching based semi-supervised video
object segmentation, where the target object masks in the first frame are provided. Existing …

Current state-of-the-art approaches for Semi-supervised Video Object Segmentation (Semi-
VOS) propagates information from previous frames to generate segmentation mask for the …

Many of the recent successful methods for video object segmentation (VOS) are overly
complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of …

Semi-supervised video object segmentation (VOS) aims to densely track certain designated
objects in videos. One of the main challenges in this task is the existence of background …

We propose a novel solution for semi-supervised video object segmentation. By the nature
of the problem, available cues (eg video frame (s) with object masks) become richer with the …

The popular unsupervised video object segmentation methods fuse the RGB frame and
optical flow via a two-stream network. However, they cannot handle the distracting noises in …

Recently, several spatial-temporal memory-based methods have verified that storing
intermediate frames and their masks as memory are helpful to segment target objects in …

This paper conducts a systematic study on the role of visual attention in Unsupervised Video
Object Segmentation (UVOS) tasks. By elaborately annotating three popular video …

Video object segmentation (VOS) is a highly challenging problem since the initial mask,
defining the target object, is only given at test-time. The main difficulty is to effectively handle …