DARTer: Dynamic Adaptive Representation Tracker for Nighttime UAV Tracking

TL;DR

DARTer is an end-to-end nighttime UAV tracking framework that adaptively fuses multi-perspective features and activates transformer layers for improved robustness and efficiency in challenging illumination and viewpoint conditions.

Contribution

The paper introduces DARTer, a novel tracker that employs dynamic feature fusion and adaptive transformer activation, reducing computational costs while enhancing tracking performance in nighttime UAV scenarios.

Findings

Outperforms state-of-the-art trackers on multiple benchmarks.

Effectively balances tracking accuracy and computational efficiency.

Eliminates complex multi-task loss functions for streamlined training.

Abstract

Nighttime UAV tracking presents significant challenges due to extreme illumination variations and viewpoint changes, which severely degrade tracking performance. Existing approaches either rely on light enhancers with high computational costs or introduce redundant domain adaptation mechanisms, failing to fully utilize the dynamic features in varying perspectives. To address these issues, we propose \textbf{DARTer} (\textbf{D}ynamic \textbf{A}daptive \textbf{R}epresentation \textbf{T}racker), an end-to-end tracking framework designed for nighttime UAV scenarios. DARTer leverages a Dynamic Feature Blender (DFB) to effectively fuse multi-perspective nighttime features from static and dynamic templates, enhancing representation robustness. Meanwhile, a Dynamic Feature Activator (DFA) adaptively activates Vision Transformer layers based on extracted features, significantly improving efficiency by reducing redundant computations. Our model eliminates the need for complex multi-task loss functions, enabling a streamlined training process. Extensive experiments on multiple nighttime UAV tracking benchmarks demonstrate the superiority of DARTer over state-of-the-art trackers. These results confirm that DARTer effectively balances tracking accuracy and efficiency, making it a promising solution for real-world nighttime UAV tracking applications.