Object tracking is a fundamental computer vision problem that refers to a set of methods
proposed to precisely track the motion trajectory of an object in a video. Multiple Object …

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 …

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 …

Efficient and accurate 3D multiobject tracking (MOT) is essential for autonomous driving.
However, existing methods still struggle with multiobject occlusion, in which interruptions or …

In the existing literature, most 3D multi-object tracking algorithms based on the tracking-by-
detection framework employed deterministic tracks and detections for similarity calculation in …

Abstract Three-dimensional (3D) multiobject tracking (MOT) is an essential perception task
for autonomous vehicles (AVs). Studies have indicated that multimodal data fusion can …

LiDAR-based Multi-Object Tracking (MOT) is a critical technology employed in various
autonomous systems, including self-driving vehicles and autonomous delivery robots. In this …

3D Multi-Object Tracking (MOT) in dynamic point cloud sequences is a fundamental
research problem for several downstream tasks such as motion planning and action …

In the classical tracking-by-detection (TBD) paradigm, detection and tracking are separately
and sequentially conducted, and data association must be properly performed to achieve …

Most existing studies performed video denoising by using multiple adjacent noisy frames to
recover one clean frame; however, despite achieving relatively good quality for each …