Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …

The nascent applicability of multi-camera tracking (MCT) in numerous real-world
applications makes it a significant computer vision problem. While visual tracking of objects …

Multiple Object Tracking (MOT) plays an important role in solving many fundamental
problems in video analysis and computer vision. Most MOT methods employ two steps …

Standardized benchmarks are crucial for the majority of computer vision applications.
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …

Tracking objects over long videos effectively means solving a spectrum of problems, from
short-term association for un-occluded objects to long-term association for objects that are …

This paper revisits the classical multiple hypotheses tracking (MHT) algorithm in a tracking-
by-detection framework. The success of MHT largely depends on the ability to maintain a …

In the recent past, the computer vision community has developed centralized benchmarks
for the performance evaluation of a variety of tasks, including generic object and pedestrian …

We present a novel approach to online multi-target tracking based on recurrent neural
networks (RNNs). Tracking multiple objects in real-world scenes involves many challenges …

Abstract Online Multi-Object Tracking (MOT) has wide applications in time-critical video
analysis scenarios, such as robot navigation and autonomous driving. In tracking-by …

The recent trend in multiple object tracking (MOT) is heading towards leveraging deep
learning to boost the tracking performance. However, it is not trivial to solve the data …