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 intelligent analysis of video data is currently in wide demand because a video is a major
source of sensory data in our lives. Text is a prominent and direct source of information in …

We introduce here a large tracking database that offers an unprecedentedly wide coverage
of common moving objects in the wild, called GOT-10k. Specifically, GOT-10k is built upon …

Visual representation plays an important role in visual object tracking. However, few works
study the tracking-specified representation learning method. Most trackers directly use …

How to effectively learn temporal variation of target appearance, to exclude the interference
of cluttered background, while maintaining real-time response, is an essential problem of …

In recent years, many tracking algorithms achieve impressive performance via fusing
multiple types of features, however, most of them fail to fully explore the context among the …

With efficient appearance learning models, discriminative correlation filter (DCF) has been
proven to be very successful in recent video object tracking benchmarks and competitions …

In this paper we present a tracker, which is radically different from state-of-the-art trackers:
we apply no model updating, no occlusion detection, no combination of trackers, no …

Abstract Machine learning techniques are often used in computer vision due to their ability to
leverage large amounts of training data to improve performance. Unfortunately, most generic …

Abstract The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-
term single-object visual trackers that do not apply pre-learned models of object …