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

Multi-object tracking aims to recover the object trajectories, given multiple detections in
video frames. Object feature extraction and similarity metric are the two keys to reliably …

We propose a novel real-time multiple pedestrian tracker for videos acquired from both static
and moving cameras in unconstrained real-world environment. In such scenes, trackers …

We propose a novel online multiple object tracker taking structure information into account.
State-of-the-art multi-object tracking (MOT) approaches commonly focus on discriminative …

Multiple Object Tracking (MOT) has attracted increasing attention due to its academic and
commercial potential. However, it still remains challenging due to factors like data …