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arXiv AI By Geoffroy Keime, Nicolas Cuperlier, Benoit R. Cottereau

REACT: A Fully Spiking State-Space Model for Real-Time Event-Driven Temporal Perception

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REACT is a fully spiking state‑space model that processes raw event‑camera data one event at a time, avoiding temporal accumulation and its associated delay. It employs a complex‑valued spiking neuron (C‑SiLIF) whose dynamics are driven by the inter‑event interval, enabling continuous‑time state updates at microsecond resolution. Evaluated on gesture recognition and time‑to‑collision estimation, REACT achieves low latency (4.6 ms) and high accuracy, supports anytime prediction, zero‑shot transfer, and INT8 quantization, dramatically reducing energy consumption.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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