Unmanned aerial vehicles

Spatial Reliability Enhanced Correlation Filter: An Efficient Approach for Real-Time UAV Tracking

Traditional discriminative correlation filter (DCF) has received great popularity due to its high computational efficiency. However, the lightweight framework of DCF cannot promise robust performance when the tracker faces appearance variations …

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 …

SiamAPN++: Siamese Attentional Aggregation Network for Real-Time UAV Tracking

Recently, the Siamese-based method has stood out from multitudinous tracking methods owing to its state-of-the-art (SOTA) performance. Nevertheless, due to various special challenges in UAV tracking, e.g., severe occlusion, and fast motion, most …

ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking

Prior correlation filter (CF)-based tracking methods for unmanned aerial vehicles (UAVs) have virtually focused on tracking in the daytime. However, when the night falls, the trackers will encounter more harsh scenes, which can easily lead to …

Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid Label

Unmanned aerial vehicle (UAV) based visual tracking has been confronted with numerous challenges, e.g., object motion and occlusion. These challenges generally bring about target appearance mutations and cause tracking failure. However, most …

Online Recommendation-based Convolutional Features for Scale-Aware Visual Tracking

In this paper, we develop an online learning-based visual tracking framework that can optimize the target model and estimate the scale variation for object tracking. We propose a recommender-based tracker, which is capable of selecting the …

Siamese Anchor Proposal Network for High-Speed Aerial Tracking

In the domain of visual tracking, most deep learning-based trackers highlight the accuracy but casting aside efficiency, thereby impeding their real-world deployment on mobile platforms like the unmanned aerial vehicle (UAV). In this work, a novel …

Learning Dynamic Regression with Automatic Distractor Repression for Real-Time UAV Tracking

With high efficiency and efficacy, the trackers based on the discriminative correlation filter have experienced rapid development in the field of unmanned aerial vehicle (UAV) over the past decade. In literature, these trackers aim at solving a …

Augmented Memory for Correlation Filters in Real-Time UAV Tracking

The outstanding computational efficiency of discriminative correlation filter (DCF) fades away with various complicated improvements. Previous appearances are also gradually forgotten due to the exponential decay of historical views in traditional …