Deep learning (DL) has made breakthroughs in many computer vision tasks and also in
visual tracking. From the beginning of the research on the automatic acquisition of high …

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 …

Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics
overemphasize the importance of either detection or association. To address this, we …

In the last decade, crowd counting and localization attract much attention of researchers due
to its wide-spread applications, including crowd monitoring, public safety, space design, etc …

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a
new pair of precision-recall measures of performance that treats errors of all types uniformly …

This paper addresses the problem of estimating and tracking human body keypoints in
complex, multi-person video. We propose an extremely lightweight yet highly effective …

Object tracking and 3D reconstruction are often performed together, with tracking used as
input for reconstruction. However, the obtained reconstructions also provide useful …

State-of-the-art multi-object tracking (MOT) methods follow the tracking-by-detection
paradigm, where object trajectories are obtained by associating per-frame outputs of object …

This paper proposes a novel iterative maximum weighted independent set (MWIS) algorithm
for multiple hypothesis tracking (MHT) in a tracking-by-detection framework. MHT converts …

Many state-of-the-art approaches to multi-object tracking rely on detecting them in each
frame independently, grouping detections into short but reliable trajectory segments, and …