Detection and tracking meet drones challenge
Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …
range of applications, including agriculture, aerial photography, and surveillance …
Recent advances in embedding methods for multi-object tracking: a survey
Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …
obtain entire moving trajectories. With the advancement of deep neural networks and the …
Giaotracker: A comprehensive framework for mcmot with global information and optimizing strategies in visdrone 2021
Y Du, J Wan, Y Zhao, B Zhang… - Proceedings of the …, 2021 - openaccess.thecvf.com
In recent years, algorithms for multiple object tracking tasks have benefited from great
progresses in deep models and video quality. However, in challenging scenarios like drone …
progresses in deep models and video quality. However, in challenging scenarios like drone …
Toward real-time uav multi-target tracking using joint detection and tracking
T Keawboontan, M Thammawichai - IEEE Access, 2023 - ieeexplore.ieee.org
Multiple object tracking (MOT) of unmanned aerial vehicle (UAV) systems is essential for
both defense and civilian applications. As drone technology moves towards real-time …
both defense and civilian applications. As drone technology moves towards real-time …
Multiple object tracking of drone videos by a temporal-association network with separated-tasks structure
The task of multi-object tracking via deep learning methods for UAV videos has become an
important research direction. However, with some current multiple object tracking methods …
important research direction. However, with some current multiple object tracking methods …
Automatic vehicle counting and tracking in aerial video feeds using cascade region-based convolutional neural networks and feature pyramid networks
Y Youssef, M Elshenawy - Transportation Research Record, 2021 - journals.sagepub.com
Unmanned aerial vehicles, or drones, are poised to solve many problems associated with
data collection in complex urban environments. Drones are easy to deploy, have a great …
data collection in complex urban environments. Drones are easy to deploy, have a great …
Global-local and occlusion awareness network for object tracking in UAVs
L Shi, Q Zhang, B Pan, J Zhang… - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Multiobject tracking in unmanned aerial vehicle (UAV) scenes is a crucial task with
numerous applications across various domains. The goal of this task is to track multiple …
numerous applications across various domains. The goal of this task is to track multiple …
Visdrone-mot2020: The vision meets drone multiple object tracking challenge results
Abstract The Vision Meets Drone (VisDrone2020) Multiple Object Tracking (MOT) is the third
annual UAV MOT tracking evaluation activity organized by the VisDrone team, in …
annual UAV MOT tracking evaluation activity organized by the VisDrone team, in …
Adaptive learning-enhanced lightweight network for real-time vehicle density estimation
LX Qin, HM Sun, XM Duan, CY Che, RS Jia - The Visual Computer, 2024 - Springer
In order to maintain competitive density estimation performance, most of the existing works
design cumbersome network structures to extract and refine vehicle features, resulting in …
design cumbersome network structures to extract and refine vehicle features, resulting in …
Yolodrone+: Improved yolo architecture for object detection in uav images
The performance of object detection algorithms running on images taken from Unmanned
Aerial Vehicles (UAVs) remains limited when compared to the object detection algorithms …
Aerial Vehicles (UAVs) remains limited when compared to the object detection algorithms …