SDTrack: A Baseline for Event-based Tracking via Spiking Neural Networks
Researchers have developed SDTrack, a novel pipeline for event-based object tracking using Spiking Neural Networks (SNNs). This approach integrates a Transformer-based tracker with a unique event frame aggregation method called Global Trajectory Prompt (GTP). The system operates end-to-end, achieving state-of-the-art accuracy on multiple datasets with significantly fewer parameters and lower energy consumption compared to existing methods. AI
IMPACT Establishes a new baseline for event-based tracking, potentially improving efficiency and performance in neuromorphic vision systems.