AI RESEARCH
Fully Spiking Neural Networks with Target Awareness for Energy-Efficient UAV Tracking
arXiv CS.CV
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ArXi:2603.27493v1 Announce Type: new Spiking Neural Networks (SNNs), characterized by their event-driven computation and low power consumption, have shown great potential for energy-efficient visual tracking on unmanned aerial vehicles (UAVs). However, existing efficient SNN-based trackers heavily rely on costly event cameras, limiting their deployment on UAVs. To address this limitation, we propose STATrack, an efficient fully spiking neural network framework for UAV visual tracking using RGB inputs only.