In recent years, pedestrian detection and tracking have significant progress in both
performance and latency. However, detecting and tracking pedestrian human-body in highly …

There has been a growing interest in leveraging state of the art deep learning techniques for
tracking objects in recent years. Most of this work focuses on using redundant appearance …

The You Only Look Once (YOLO) series has been widely adopted across various domains.
With the increasing prevalence of continuous satellite observation, the resulting video …

Though achieving aggressive progress, there are only a few explorations on the robustness
of Multi-Object Tracking (MOT) trackers. Most of the existing MOT research focuses on …

Standardized benchmarks are crucial for the majority of computer vision applications.
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …

Artificial intelligence-based surveillance system, one of the essential systems for smart cities,
plays a critical role in ensuring the safety and well-being of individuals. In this paper, we …

This work aims to show the new approaches in embedded vision dedicated to object
detection and tracking for drone visual control. Object/Pedestrian detection has been carried …

Over the years, object tracking and detection has emerged as one of the most important
aspects of UAV applications such as surveillance, reconnaissance, etc. In our paper, we …

People tracking in crowded real-world scenes is challenging due to frequent and long-term
occlusions. Recent tracking methods obtain the image evidence from object (people) …

With the rapid development of deep learning, object detection and tracking play a vital role
in today's society. Being able to identify and track all the pedestrians in the dense crowd …