Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Object class detection, also known as category-level object detection, has become one of
the most focused areas in computer vision in the new century. This article attempts to …

This paper addresses the problem of 3D human pose estimation in the wild. A significant
challenge is the lack of training data, ie, 2D images of humans annotated with 3D poses …

Despite all the significant advances in pedestrian detection brought by computer vision for
driving assistance, it is still a challenging problem. One reason is the extremely varying …

Advanced driver assistance systems (ADASs), and particularly pedestrian protection
systems (PPSs), have become an active research area aimed at improving traffic safety. The …

Pedestrian detection is a rapidly evolving area in computer vision with key applications in
intelligent vehicles, surveillance, and advanced robotics. The objective of this paper is to …

This paper introduces a general active-learning framework for robust on-road vehicle
recognition and tracking. This framework takes a novel active-learning approach to building …

State-of-the-art methods for human detection and pose estimation require many training
samples for best performance. While large, manually collected datasets exist, the captured …

Pedestrian detection is of paramount interest for many applications. Most promising
detectors rely on discriminatively learnt classifiers, ie, trained with annotated samples …

Active safety systems hold great potential for reducing accident frequency and severity by
warning the driver and/or exerting automatic vehicle control ahead of crashes. This paper …