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arXiv Computer Vision By Mikihiro Ikura, Luna Gava, Jiahang Wu, Chiara Bartolozzi, Arren Glover

An Event Preserving Velocity Invariant Representation for Event Cameras

Read the original on arXiv Computer Vision →

The paper introduces SCARF, a real‑time velocity‑invariant representation for event cameras that preserves raw events while handling fast motion, stationary scenes, and independently moving objects. Unlike previous methods that convert events into image‑like forms and lose temporal detail, SCARF maintains temporal information and achieves state‑of‑the‑art performance in computational efficiency and representation quality.

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 Computer Vision.

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