UAV tracking

Towards Real-World Visual Tracking with Temporal Contexts

Visual tracking has made significant improvements in the past few decades. Most existing state-of-the-art trackers 1) merely aim for performance in ideal conditions while overlooking the real-world conditions; 2) adopt the tracking-by-detection …

Adversarial Blur-Deblur Network for Robust UAV Tracking

Unmanned aerial vehicle (UAV) tracking has been widely applied in real-world applications such as surveillance and monitoring. However, the inherent high maneuverability and agility of UAV often lead to motion blur, which can impair the visual …

Boosting UAV Tracking with Voxel-Based Trajectory-Aware Pre-Training

Siamese network-based object tracking has remarkably promoted the automatic capability for highly-maneuvered unmanned aerial vehicles (UAVs). However, the leading-edge tracking framework often depends on template matching, making it trapped when …

End-to-End Feature Decontaminated Network for UAV Tracking

Object feature pollution is one of the burning issues in vision-based UAV tracking, commonly caused by occlusion, fast motion, and illumination variation. Due to the contaminated information in the polluted object features, most trackers fail to …

PVT

Predictive visual tracking (PVT) is a latency-aware benchmark jointly assessing the tracking accuracy and efficiency of trackers.