Current popular online multi-object tracking (MOT) solutions apply single object trackers
(SOTs) to capture object motions, while often requiring an extra affinity network to associate …

Transformers have proven superior performance for a wide variety of tasks since they were
introduced. In recent years, they have drawn attention from the vision community in tasks …

Identity switches caused by inter-object interactions remain a critical problem for multi-player
tracking in real-world sports video analysis. Existing approaches utilizing the appearance …

Multi-object tracking (MOT) is an essential task in the computer vision field. With the fast
development of deep learning technology in recent years, MOT has achieved great …

Siamese networks have achieved great success in object tracking due to the balance of
precision and speed. However, Siamese trackers usually utilize the local feature of the last …

As an intermediate task in computer vision, multiple pedestrian tracking (MPT) aiming at
tracking the pedestrians from a given video, has attracted attention due to its potential …

Online multi-object tracking aims at generating the trajectories for multiple objects in the
surveillance scene. It remains a challenging problem in crowded scenes because objects …

Abstract Multi-Object Tracking (MOT) has been one of the most important topics in computer
vision. The traditional tracking-by-detection framework of MOT is severely suffered from the …

Multiple object tracking (MOT) has gained increasing attention due to its academic and
commercial interests in computer vision tasks. Most of the existing state-of-the-art MOT …

Multiple live videos are streamed to the security room in the video surveillance system of a
museum, shopping mall, plaza, etc. For public safety and crowd research, multi-person …