The complex dynamicity of open-world objects presents non-negligible challenges for multi-object tracking (MOT), often manifested as severe deformations, fast motion, and occlusions. Most methods that solely depend on coarse-grained object cues, such …
Object tracking is crucial for the autonomous navigation of unmanned aerial vehicles (UAVs) and has broad application in robotic automation fields. However, reliable aerial tracking remains a challenging task due to various difficulties like frequent …
Vision-based object tracking has boosted extensive autonomous applications for unmanned aerial vehicles (UAVs). However, the frequent maneuvering flight and viewpoint change are prone to cause nerve-wracking challenges, e.g., aspect ratio change and …
Visual object tracking is an essential capability of intelligent robots. Most existing approaches have ignored the online latency that can cause severe performance degradation during real-world processing. Especially for unmanned aerial vehicle, …
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 …
Low-light environments have posed a formidable challenge for robust UAV tracking even with state-of-the-art trackers since the potential image features are hard to extract under adverse light conditions. Besides, due to the low visibility, accurate …
Visual object tracking has been utilized in numerous aerial platforms, where is facing the challenges of more extremely complex conditions. To address the inefficient long-range modeling of traditional networks with fully convolutional neural …
Although the manipulating of the unmanned aerial manipulator (UAM) has been widely studied, vision-based UAM approaching, which is crucial to the subsequent manipulating, generally lacks effective design. The key to the visual UAM approaching lies in …
Temporal contexts among consecutive frames are far from been fully utilized in existing visual trackers. In this work, we present TCTrack1, a comprehensive framework to fully exploit temporal contexts for aerial tracking. The temporal contexts are …
Previous advances in object tracking mostly reported on favorable illumination circumstances while neglecting performance at nighttime, which significantly impeded the development of related aerial robot applications. This work instead develops a …