Deep semi-supervised learning is a fast-growing field with a range of practical applications.
This paper provides a comprehensive survey on both fundamentals and recent advances in …

Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …

Appearance and motion are two important sources of information in video object
segmentation (VOS). Previous methods mainly focus on using simplex solutions, lowering …

The ability to capture inter-frame dynamics has been critical to the development of video
salient object detection (VSOD). While many works have achieved great success in this field …

Optical flow is an easily conceived and precious cue for advancing unsupervised video
object segmentation (UVOS). Most of the previous methods directly extract and fuse the …

Humans tend to mine objects by learning from a group of images or several frames of video
since we live in a dynamic world. In the computer vision area, many researchers focus on co …

Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

Referring video object segmentation aims to predict foreground labels for objects referred by
natural language expressions in videos. Previous methods either depend on 3D ConvNets …

We propose a new video camouflaged object detection (VCOD) framework that can exploit
both short-term dynamics and long-term temporal consistency to detect camouflaged objects …

In this paper, we study the problem of salient object detection (SOD) for RGB-D images
using both color and depth information. A major technical challenge in performing salient …