1

PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework

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, …

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 …

HighlightNet: Highlighting Low-Light Potential Features for Real-Time UAV Tracking

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 …

Local Perception-Aware Transformer for Aerial Tracking

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 …

Siamese Object Tracking for Vision-Based UAM Approaching with Pairwise Scale-Channel Attention

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 …

TCTrack: Temporal Contexts for Aerial Tracking

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 …

Unsupervised Domain Adaptation for Nighttime Aerial Tracking

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 …

Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV Tracking

Visual tracking is adopted to extensive unmanned aerial vehicle (UAV)-related applications, which leads to a highly demanding requirement on the robustness of UAV trackers. However, adding imperceptible perturbations can easily fool the tracker and …

HiFT: Hierarchical Feature Transformer for Aerial Tracking

Siamese-based visual tracking methods generally execute the classification and regression of the target object based on the similarity maps. However, existing works either solely employ a single map generated by the last convolutional layer which …

DarkLighter: Light Up the Darkness for UAV Tracking

Recent years have witnessed the fast evolution and promising performance of the convolutional neural network (CNN)-based trackers, which aim at imitating biological visual systems. However, current CNN-based trackers can hardly generalize well to …