In multi-target tracking, object interactions and occlusions are two significant factors that
affect tracking performance. To settle this, we propose an identity association network …

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with
each incoming frame and the information provided up to the moment. It still remains a …

Multi-object tracking (MOT), which is crucial for computer vision and video processing, has
immense potential for improvement. Traditional tracking-by-detection approaches include …

Abstract Online two-dimensional (2D) multi-object tracking (MOT) is a challenging task when
the objects of interest have similar appearances. In that case, the motion of objects is …

A data association, which links detections in consecutive frames, is a key issue in multi-
object tracking (MOT). For robust data association in a complex scene, a common approach …

Most of the existing Multi-Object Tracking (MOT) approaches follow the Tracking-by-
Detection and Data Association paradigm, in which objects are firstly detected and then …

Abstract Multi-Object Tracking (MOT) encompasses various tracking scenarios each
characterized by unique traits. Effective trackers should demonstrate a high degree of …

Multiple object tracking has improved drastically in recent years due to one-shot tracking
methods. These methods design joint-detection-and-tracking structures to achieve real-time …

Recent progresses in model-free single object tracking (SOT) algorithms have largely
inspired applying SOT to multi-object tracking (MOT) to improve the robustness as well as …

This paper proposes a generic multi-object tracking (MOT) algorithm that is robust to
unexpected motion changes for generic objects. Deep learning has dramatically been …