Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …

Safety assessment of road sections and networks have historically relied on police-reported
crash data. These data have several noteworthy and significant shortcomings, including …

Multi-object tracking (MOT) is an important problem in computer vision which has a wide
range of applications. Formulating MOT as multi-task learning of object detection and re-ID …

Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …

The problem of tracking multiple objects in a video sequence poses several challenging
tasks. For tracking-by-detection, these include object re-identification, motion prediction and …

Graphs offer a natural way to formulate Multiple Object Tracking (MOT) within the tracking-by-
detection paradigm. However, they also introduce a major challenge for learning methods …

Standardized benchmarks have been crucial in pushing the performance of computer vision
algorithms, especially since the advent of deep learning. Although leaderboards should not …

Object detection and data association are critical components in multi-object tracking (MOT)
systems. Despite the fact that the two components are dependent on each other, prior works …

Multi-object tracking is a fundamental vision problem that has been studied for a long time.
As deep learning brings excellent performances to object detection algorithms, Tracking by …

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 …