Despite the numerous developments in object tracking, further development of current
tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data …

Visual tracking is challenging as target objects often undergo significant appearance
changes caused by deformation, abrupt motion, background clutter and occlusion. In this …

This paper presents a framework for simultaneously tracking, learning and parsing objects
with a hierarchical and compositional And-Or graph (AOG) representation. The AOG is …

The newly proposed correlation filter based trackers can achieve appealing performance
despite their great simplicity and superior speed. However, this kind of object trackers is not …

Convolutional Neural Network (CNN) based methods have shown significant performance
gains in the problem of visual tracking in recent years. Due to many uncertain changes of …

In recent years, SiamFC-based trackers have received much attention because of their great
potentials in balancing tracking accuracy and speed. However, the robustness of most such …

Convolution Neural Network (CNN) features have been widely used in visual tracking due to
their powerful representation. As an important component of CNN, the pooling layer plays a …

Correlation filter and Siamese network based methods are popular in visual tracking due to
their competitive performance in both precision and efficiency. However, Siamese network …

The problem of tracking people in a video stream with the aim of counting them is studied.
Modern video surveillance systems, such as the Moscow video surveillance system, use …

Object tracking is a hot topic in computer vision. The significantly developed satellite video
technology makes object tracking in satellite videos possible. In recent years, Convolutional …