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 …

Advancements in the development of deep learning and computer vision-based approaches
have the potential to provide managers and engineers with the ability to improve the safety …

Perception and prediction are two separate modules in the existing autonomous driving
systems. They interact with each other via hand-picked features such as agent bounding …

This work proposes an end-to-end multi-camera 3D multi-object tracking (MOT) framework. It
emphasizes spatio-temporal continuity and integrates both past and future reasoning for …

3D multi-object tracking (MOT) is an essential component for many applications such as
autonomous driving and assistive robotics. Recent work on 3D MOT focuses on develo** …

Abstract 3D Multi-object tracking (MOT) is crucial to autonomous systems. Recent work uses
a standard tracking-by-detection pipeline, where feature extraction is first performed …

Multi-sensor perception is crucial to ensure the reliability and accuracy in autonomous
driving system, while multi-object tracking (MOT) improves that by tracing sequential …

Vehicle 3D extents and trajectories are critical cues for predicting the future location of
vehicles and planning future agent ego-motion based on those predictions. In this paper, we …

Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-
based autonomous driving system. It involves modeling 3D dynamic objects in complex …

Siamese network based trackers formulate 3D single object tracking as cross-correlation
learning between point features of a template and a search area. Due to the large …