Unsupervised spiking feature learning for event-based pedestrian crossing detection: approaching supervised accuracy without labelled training data

arXiv:2609.31671v1 Announce Type: new Abstract: Event cameras are well suited to pedestrian crossing detection, and spiking neural networks (SNNs) can process their output natively, but current SNN detectors are trained with supervised backpropagation and therefore require costly frame-level crossi…

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1. 2026-09-29 04:00 · arXiv cs.CV
   Unsupervised spiking feature learning for event-based pedestrian crossing detection: approaching supervised accuracy without labelled training data