mlsanityData to 14 Oct 2026

Automotive Object Detection via Learning Sparse Events by Spiking Neurons

arXiv 2307.12900 ↗First posted 24 Jul 2023cs.CVcited by 5

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Abstract (arXiv)

Event-based sensors, distinguished by their high temporal resolution of 1 μs and a dynamic range of 120 dB, stand out as ideal tools for deployment in fast-paced settings like vehicles and drones. Traditional object detection techniques that utilize Artificial Neural Networks (ANNs) face challenges due to the sparse and asynchronous nature of the events these sensors capture. In contrast, Spiking Neural Networks (SNNs) offer a promising alternative, providing a temporal representation that is inherently aligned with event-based data. This paper explores the unique membrane potential dynamics of SNNs and their ability to modulate sparse events. We introduce an innovative spike-triggered adaptive threshold mechanism designed for stable training. Building on these insights, we present a specialized spiking feature pyramid network (SpikeFPN) optimized for automotive event-based object detection. Comprehensive evaluations demonstrate that SpikeFPN surpasses both traditional SNNs and advanced ANNs enhanced with attention mechanisms. Evidently, SpikeFPN achieves a mean Average Precision (mAP) of 0.477 on the GEN1 Automotive Detection (GAD) benchmark dataset, marking significant increases over the selected SNN baselines. Moreover, the efficient design of SpikeFPN ensures robust performance while optimizing computational resources, attributed to its innate sparse computation capabilities. Source codes are publicly accessible at https://github.com/EMI-Group/spikefpn.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 62 of its 102 references that are in the map. First posted on arXiv 24 Jul 2023.

Builds on

62 of 102 references.

References · 62

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38 more
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  3. 2019Surrogate Gradient Learning in Spiking Neural Networkscited by 626
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  25. 2021A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibrationcited by 117
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  27. 2020Event-based Asynchronous Sparse Convolutional Networkscited by 104
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50 most cited of 62 All 62 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 2.

5 papers.

  1. 2025Hybrid Spiking Vision Transformer for Object Detection with Event Camerascited by 7
  2. 2024Efficient Event-Based Object Detection: A Hybrid Neural Network with Spatial and Temporal Attentioncited by 6
  3. 2024PowerYOLO: Mixed Precision Model for Hardware Efficient Object Detection with Event Datacited by 2
  4. 2026Neuromorphic Object Detection: An In-Depth Study and Future Directionscited by 0
  5. 2026Sequence-SOD: Bio-inspired Sequence-aware Spiking ObjectDetection for Event Camerascited by 0