This paper provides a literature review of some of the most important concepts, techniques,
and methodologies used within autonomous car systems. Specifically, we focus on two …

This literature review focuses on three important aspects of an autonomous car system:
tracking (assessing the identity of the actors such as cars, pedestrians or obstacles in a …

To exploit rich information from unlabeled data, in this work, we propose a novel self-
supervised framework for visual tracking which can easily adapt the state-of-the-art …

Event cameras, which are asynchronous bio-inspired vision sensors, have shown great
potential in a variety of situations, such as fast motion and low illumination scenes. However …

Deep trackers have proven success in visual tracking. Typically, these trackers employ
optimally pre-trained deep networks to represent all diverse objects with multi-channel …

Discriminative correlation filters (DCFs) have shown promising tracking performance in
recent years thanks to the powerful representation ability of deep features. However, a large …

Recently, convolutional neural network (CNN) has attracted much attention in different areas
of computer vision, due to its powerful abstract feature representation. Visual object tracking …

In this paper, we continue the research cycle on the properties of convolutional neural
network-based image recognition systems and ways to improve noise immunity and …

Object trackers based on Convolution Neural Network (CNN) have achieved state-of-the-art
performance on recent tracking benchmarks, while they suffer from slow computational …

Correlation filtering based tracking model has received significant attention and achieved
great success in terms of both tracking accuracy and computational complexity. However …