Learning Efficient Transformer Representation for Siamese Tracker to UAV
Hao Wang, Xiaolou Sun, Wankou Yang, Qiang Wang · 2023
In the last few years, there has been growing recognition of the vital links between visual tracking and unmanned aerial vehicle (UAV). Questions have been raised about the feasibility of CNN-based and transformer-based trackers on UAVs. However, deep neural network modules or self-attention modules can be adversely affected when employing on UAVs for their complex architecture. In this paper, we propose an efficient transformer tracker (ET2) with a lightweight network. The study set out to examine the usability of a transformer-based tracker. Our tracker performs at frame rates far surpassing real-time, achieving the balance of precision and running speed.