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arXiv · 2609.19973

An Event Preserving Velocity Invariant Representation for Event Cameras

Mikihiro Ikura·Luna Gava·Jiahang Wu·Chiara Bartolozzi·Arren Glover
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Abstract

Event cameras provide low-latency, high temporal resolution perception for real-time vision tasks such as robotics.The novel circuitry (i.e. asynchronous, independent pixels) that enables these advantages also introduces new algorithmic challenges. Velocity-invariant representations alleviate missing observations under slow motion and motion blur under fast motion, but most discard temporal information by converting events into image-like representations. We propose Set of Centre Active Receptive Fields (SCARF), a real-time velocity-invariant representation that preserves raw events while consistently handling fast motion, stationary scenes, and independently moving objects. SCARF achieves state-of-the-art performance in both computational efficiency and representation quality.

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Mikihiro Ikura, Luna Gava, Jiahang Wu, Chiara Bartolozzi, Arren Glover. 2026-09-17. An Event Preserving Velocity Invariant Representation for Event Cameras. https://arxiv.org/abs/2609.19973

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