Multi-view multi-human association and tracking (MvMHAT), is an emerging yet important
problem for multi-person scene video surveillance, aiming to track a group of people over …

Multiple object tracking (MOT), as a typical application scenario of computer vision, has
attracted significant attention from both academic and industrial communities. With its rapid …

Recent advances in Multi-Object Tracking (MOT) have achieved remarkable success in
short-term association within the decoupled tracking-by-detection online paradigm …

In this paper, we address the challenge of multi-object tracking (MOT) in moving Unmanned
Aerial Vehicle (UAV) scenarios, where irregular flight trajectories, such as hovering, turning …

Increasing the annotation efficiency of trajectory annotations from videos has the potential to
enable the next generation of data-hungry tracking algorithms to thrive on large-scale …

Multi-object tracking (MOT) on static platforms, such as by surveillance cameras, has
achieved significant progress, with various paradigms providing attractive performances …

Abstract Knowledge Distillation (KD) transfers knowledge from a larger and well-trained
teacher network to a smaller and trainable student network. Existing KD methods are divided …

Download Copy BibTeX@ Article {Lu2024, author={Zijia Lu and Bing Shuai and Yanbei
Chen and Zhenlin Xu and Davide Modolo}, title={Self-supervised multi-object tracking with …

In high-altitude scenarios, targets tend to occupy a small number of pixels within the UAV's
field of view, resulting in substantial errors when identity recognition is attempted based …

This paper introduces a novel framework to learn data association for multi-object tracking in
a self-supervised manner. Fully-supervised learning methods are known to achieve …