Recently, Multi-Object Tracking (MOT) has attracted rising attention, and accordingly,
remarkable progresses have been achieved. However, the existing methods tend to use …

Kalman filter (KF) based methods for multi-object tracking (MOT) make an assumption that
objects move linearly. While this assumption is acceptable for very short periods of …

Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …

Multiple object tracking gained a lot of interest from researchers in recent years, and it has
become one of the trending problems in computer vision, especially with the recent …

Multi-object tracking in unmanned aerial vehicle (UAV) videos is an important vision task
and can be applied in a wide range of applications. However, conventional multi-object …

In the recent literature, on the one hand, many 3D multi-object tracking (MOT) works have
focused on tracking accuracy and neglected computation speed, commonly by designing …

3D Multi-object tracking (MOT) ensures consistency during continuous dynamic detection,
conducive to subsequent motion planning and navigation tasks in autonomous driving …

Abstract 3D object tracking is a critical task in autonomous driving systems. It plays an
essential role for the system's awareness about the surrounding environment. At the same …

Cattle monitoring is an essential aspect of precision farming, and recent advancements have
greatly contributed to understanding cattle behavior using wearable devices like ear tags …

Mainstream multi-object tracking methods exploit appearance information and/or motion
information to achieve interframe association. However, dealing with similar appearance …