English(EN) Sequence-SOD: Bio-inspired Sequence-aware Spiking ObjectDetection for Event Cameras

Sequence-SOD：仿生学SNN目标检测器用于事件相机，提高准确性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-30 04:00

研究人员开发了Sequence-SOD，一种用于事件相机的、利用仿生学脉冲神经网络（SNN）的新型目标检测系统。与处理孤立事件间隔的先前方法不同，Sequence-SOD处理扩展的事件序列，跨时间步保留神经状态，以更好地利用时间信息。这种序列感知方法提高了检测精度，在应用数据增强的情况下，在Gen1汽车检测数据集上实现了26.88的平均精度均值（mAP），而单间隔训练的mAP为23.38。该系统可以以40 Hz的理论预测频率运行，突显了序列感知训练对基于事件的SNN检测的好处。 AI

影响通过SNN更好地利用时间数据，增强了事件相机的目标检测能力。

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Katharina Bendig, Ren\'e Schuster, Didier Stricker · 2026-07-30 04:00

Sequence-SOD：受生物启发的序列感知脉冲事件相机目标检测

arXiv:2607.26703v1 Announce Type: new Abstract: Event cameras follow a retina-inspired sensing principle, reporting local intensity changes asynchronously with hightemporal resolution and a wide dynamic range. Spiking Neural Networks (SNNs) complement these sparse event streams t…

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Sequence-SOD：受生物启发的序列感知脉冲事件相机目标检测

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