Most multi-object tracking methods have achieved good results in tracking multiple
pedestrians with Kalman filter, but their tracking performance in crowded scenes is still poor …

Aiming at the problems of frequent identity switches (IDs) and trajectory interruption of multi-
pedestrian tracking algorithms in dense scenes, this paper proposes a multi-pedestrian …

Object tracking is divided into single-object tracking (SOT) and multi-object tracking (MOT).
MOT aims to maintain the identities of multiple objects across a series of continuous video …

Multi-pedestrian trackers perform well when targets are clearly visible making the
association task quite easy. However, when heavy occlusions are present, a mechanism to …

Recently, one-shot trackers, which integrate multi-tasks into a unified network, achieve good
performances in multi-object video tracking and successfully handle the core challenge of …

Multiple pedestrian tracking faces the challenge of tracking pedestrians in the presence of
occlusion. Existing methods suffer from inaccurate motion estimation, appearance feature …

Abstract Multi-Object Tracking (MOT) is a challenging research area in computer vision with
significant practical applications. With the advent of deep neural networks, significant …

The performance of pedestrian multiple object tracking (MOT), which is based on the
tracking-by-detection framework, is exceedingly susceptible to the quality of detection …

One of the biggest challenges in multi-pedestrian tracking arises in crowds, where missing
detections can lead to wrong track-detection assignments, especially under heavy …

Multiobject tracking (MOT) in video sequences has gradually become one of the most
essential fields in computer vision tasks. As the use of two separate models for feature …