Abstract Multi-Camera People Tracking (MCPT) is a crucial task in intelligent surveillance
systems. However, it presents significant challenges due to issues such as heavy occlusion …

Though achieving aggressive progress, there are only a few explorations on the robustness
of Multi-Object Tracking (MOT) trackers. Most of the existing MOT research focuses on …

Nano-sized unmanned aerial vehicles (UAVs) have been attracting growing attention from
both academia and industry with their compact and versatile nature. With the size of merely …

One of the biggest challenges in multi-pedestrian tracking arises in crowds, where missing
detections can lead to wrong track-detection assignments, especially under heavy …

Pedestrian target tracking is an important problem in the field of computer vision. To address
low tracking accuracy and tracking errors in pedestrian target tracking. This paper …

Multiple-object tracking (MOT) is a fundamental task in computer vision and is widely
applied across various domains. However, its algorithms remain somewhat immature in …

The process of object tracking involves consistently identifying each instance across frames
depending on initial set of object detection (s). Moreover, in multiple object tracking (MOT) …

Multiple pedestrian tracking (MPT) has gained significant attention due to its huge potential
in a commercial application. It aims to predict multiple pedestrian trajectories and maintain …

Deep learning methods have led to remarkable progress in multiple object tracking (MOT).
However, when tracking in crowded scenes, existing methods still suffer from both …

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