Multi-object tracking (MOT) is pivotal for under-standing environments in which unmanned
vehicles function. The Joint Detection and Embedding (JDE) paradigm, merging target …

Multiobject tracking (MOT) is a fundamental problem in computer vision with numerous
applications, such as intelligent surveillance and automated driving. Despite the significant …

Abstract The Smart City is a hot topic at present. Pedestrian tracking and behavior analysis
play an important role in Smart City system. Therefore, it is urgent to design an universal and …

Motion-based association for Multi-Object Tracking (MOT) has recently re-achieved
prominence with the rise of powerful object detectors. Despite this, little work has been done …

Multi-Object Tracking (MOT) is a crucial computer vision task that aims to predict the
bounding boxes and identities of objects simultaneously. While state-of-the-art methods …

Multi-object tracking is a vital component in various robotics and computer vision
applications. However, existing multi-object tracking techniques trade off computation …

Multi-object Tracking is an important issue that has been widely investigated in computer
vision. However, in practical applications, moving targets are often occluded due to complex …

In detection-based multi-object tracking (MOT), one challenging problem is to design a
robust affinity model for data association. Moreover, since these approaches entirely rely on …

The current popular one-shot multi-object tracking (MOT) algorithms are dominated by the
joint detection and embedding paradigm, which have high inference speeds and accuracy …

Multi-object pedestrian tracking plays a crucial role in autonomous driving systems, enabling
accurate perception of the surrounding environment. In this paper, we propose a …