Recently, deep learning has achieved great success in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …

The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Object tracking is one of the most important components in numerous applications of
computer vision. While much progress has been made in recent years with efforts on sharing …

Correlation Filter-based trackers have recently achieved excellent performance, showing
great robustness to challenging situations exhibiting motion blur and illumination changes …

This paper investigates long-term tracking of unknown objects in a video stream. The object
is defined by its location and extent in a single frame. In every frame that follows, the task is …

Adaptive tracking-by-detection methods are widely used in computer vision for tracking
arbitrary objects. Current approaches treat the tracking problem as a classification task and …

It is a challenging task to develop effective and efficient appearance models for robust object
tracking due to factors such as pose variation, illumination change, occlusion, and motion …

In this paper, we address the problem of long-term visual tracking where the target objects
undergo significant appearance variation due to deformation, abrupt motion, heavy …

Sparse representation has been applied to visual tracking by finding the best candidate with
minimal reconstruction error using target templates. However most sparse representation …

The boom in the capabilities and features of mobile devices, like smartphones, tablets, and
wearables, combined with the ubiquitous and affordable Internet access and the advances …