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 …

Multi-object Tracking (MOT) is very important in human surveillance, sports analytics,
autonomous driving, and cooperative robots. Current MOT methods do not perform well in …

Although single object trackers have achieved advanced performance, their large-scale
models hinder their application on limited resources platforms. Moreover, existing …

The one-shot multiple object tracking (MOT) framework simultaneously generates detected
targets and re-identification (ReID) embeddings, and employs them to associate previous …

Recent multiobject tracking (MOT) methods usually use very deep neural networks to
achieve competitive accuracy, which inevitably results in degraded inference speed. To …

The existing segmentation-based scene text detection methods mostly need complicated
post-processing, and the post-processing operation is separated from the training process …

In the field of Multi-Object Tracking (MOT), the incorporation of appearance cues into
tracking-by-detection heuristic trackers using re-identification (ReID) features has posed …

Abstract Recently, Multi-Person Tracking (MPT) has experienced significant progress due to
the emergence of innovative methods. However, congestion and occlusion persist as …

The complementary benefits from visible and thermal infrared data are extensively utilized in
various computer vision tasks, such as visual tracking and object detection, but rarely …

Most online multi-object tracking methods utilize bounding boxes and center points inherited
from detectors as the base models to represent targets. Limited performance is obtained with …