Video saliency detection (VSD) aims at fast locating the most attractive
objects/things/patterns in a given video clip. Existing VSD-related works have mainly relied …

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 …

Recent leading zero-shot video object segmentation (ZVOS) works devote to integrating
appearance and motion information by elaborately designing feature fusion modules and …

Unsupervised video object segmentation (VOS) aims to detect the most salient object in a
video sequence at the pixel level. In unsupervised VOS, most state-of-the-art methods …

Abstract Zero-shot Video Object Segmentation (ZSVOS) aims at segmenting the primary
moving object without any human annotations. Mainstream solutions mainly focus on …

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

Unsupervised video object segmentation aims to segment a target object in the video
without a ground truth mask in the initial frame. This challenging task requires extracting …

Detecting mirrors from static images has received significant research interest recently.
However, detecting mirrors over dynamic scenes is still under-explored due to the lack of a …

The optical flow guidance strategy is ideal for obtaining motion information of objects in the
video. It is widely utilized in video segmentation tasks. However, existing optical flow-based …

The existing unsupervised video object segmentation methods depend heavily on the
segmentation model trained offline on a labeled training video set, and cannot well …