Temporal modeling of objects is a key challenge in multiple-object tracking (MOT). Existing
methods track by associating detections through motion-based and appearance-based …

In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end
multi-object tracking with a pretrained object detector. Existing end-to-end methods, eg …

Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …

Abstract Multiple Object Tracking (MOT) has emerged as a hot issue in the field of computer
vision recently. MOT has academic and commercial potential in urban public security …

Object tracking belongs to active research areas in computer vision. We are interested in
matching-based trackers exploiting deep machine learning known as Siamese trackers …

Abstract Multi-Target Multi-Camera Tracking has a wide range of applications and is the
basis for many advanced inferences and predictions. This paper describes our solution to …

As an intermediate task in computer vision, multiple pedestrian tracking (MPT) aiming at
tracking the pedestrians from a given video, has attracted attention due to its potential …

Online tracking of multiple objects in videos requires strong capacity of modeling and
matching object appearances. Previous methods for learning appearance embedding …

The process of object tracking involves consistently identifying each instance across frames
depending on initial set of object detection (s). Moreover, in multiple object tracking (MOT) …

In a soccer game, the information provided by detecting and tracking brings crucial clues to
further analyze and understand some tactical aspects of the game, including individual and …