In this article, we introduce SiamMask, a framework to perform both visual object tracking
and video object segmentation, in real-time, with the same simple method. We improve the …

Recently, the U-shaped networks have been widely explored in remote sensing image
dehazing and obtained promising performance. However, most of the existing dehazing …

In this paper, we propose a progressive unsupervised learning (PUL) framework, which
entirely removes the need for annotated training videos in visual tracking. Specifically, we …

Multi-view multi-human association and tracking (MvMHAT), is an emerging yet important
problem for multi-person scene video surveillance, aiming to track a group of people over …

Self-supervised learning (SSL) performs remarkably in visual tracking since it enables the
extraction of general representations from unlabeled data and alleviates the need for …

Although Siamese trackers have recently been gradually replaced by complicated and
computationally expensive Transformer trackers, they are simpler and more applicable to …

Visual Object Tracking (VOT) is an attractive and significant research area in computer
vision, which aims to recognize and track specific targets in video sequences where the …

RGB-T tracking means that given the object position in the first frame, the tracker is trained to
predict the position of the object in consecutive frames by taking full advantage of the …

3D single object tracking in LiDAR point clouds (LiDAR SOT) plays a crucial role in
autonomous driving. Current approaches all follow the Siamese paradigm based on …

Abstract 3D single object tracking (SOT) is an indispensable part of automated driving.
Existing approaches rely heavily on large, densely labeled datasets. However, annotating …