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 presence of objects that are confusingly similar to the tracked target, poses a
fundamental challenge in appearance-based visual tracking. Such distractor objects are …

Visual tracking is fundamentally the problem of regressing the state of the target in each
video frame. While significant progress has been achieved, trackers are still prone to failures …

By decomposing the visual tracking task into two subproblems as classification for pixel
category and regression for object bounding box at this pixel, we propose a novel fully …

The training of a feature extraction network typically requires abundant manually annotated
training samples, making this a time-consuming and costly process. Accordingly, we …

While recent years have witnessed astonishing improvements in visual tracking robustness,
the advancements in tracking accuracy have been limited. As the focus has been directed …

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 …

In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object
Tracking. LaSOT consists of 1,400 sequences with more than 3.5 M frames in total. Each …

Abstract The Visual Object Tracking challenge VOT2018 is the sixth annual tracker
benchmarking activity organized by the VOT initiative. Results of over eighty trackers are …

Object tracking is still a critical and challenging problem with many applications in computer
vision. For this challenge, more and more researchers pay attention to applying deep …