mlsanityData to 7 Oct 2026

Object Detection with Spiking Neural Networks on Automotive Event Data

arXiv 2205.04339 ↗First posted 9 May 2022cs.CVcited by 79

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Abstract (arXiv)

Automotive embedded algorithms have very high constraints in terms of latency, accuracy and power consumption. In this work, we propose to train spiking neural networks (SNNs) directly on data coming from event cameras to design fast and efficient automotive embedded applications. Indeed, SNNs are more biologically realistic neural networks where neurons communicate using discrete and asynchronous spikes, a naturally energy-efficient and hardware friendly operating mode. Event data, which are binary and sparse in space and time, are therefore the ideal input for spiking neural networks. But to date, their performance was insufficient for automotive real-world problems, such as detecting complex objects in an uncontrolled environment. To address this issue, we took advantage of the latest advancements in matter of spike backpropagation - surrogate gradient learning, parametric LIF, SpikingJelly framework - and of our new textitvoxel cube event encoding to train 4 different SNNs based on popular deep learning networks: SqueezeNet, VGG, MobileNet, and DenseNet. As a result, we managed to increase the size and the complexity of SNNs usually considered in the literature. In this paper, we conducted experiments on two automotive event datasets, establishing new state-of-the-art classification results for spiking neural networks. Based on these results, we combined our SNNs with SSD to propose the first spiking neural networks capable of performing object detection on the complex GEN1 Automotive Detection event dataset.

Key facts. Cited by 79 papers in the map (data through 7 Oct 2026). Builds on 22 of its 35 references that are in the map. First posted on arXiv 9 May 2022.

Builds on

22 of 35 references.

References · 22

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2016Densely Connected Convolutional Networkscited by 6,691
  4. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  5. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  6. 2016SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model sizecited by 1,054
  7. 2019Surrogate Gradient Learning in Spiking Neural Networkscited by 604
  8. 2020Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networkscited by 340
  9. 2021Deep Residual Learning in Spiking Neural Networkscited by 326
  10. 2018SLAYER: Spike Layer Error Reassignment in Timecited by 257
  11. 2018HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classificationcited by 215
  12. 2018Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Carscited by 197
10 more
  1. 2020Learning to Detect Objects with a 1 Megapixel Event Cameracited by 184
  2. 2019Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detectioncited by 174
  3. 2020A Large Scale Event-based Detection Dataset for Automotivecited by 108
  4. 2020Event-based Asynchronous Sparse Convolutional Networkscited by 103
  5. 2021Efficient Neuromorphic Signal Processing with Loihi 2cited by 90
  6. 2018Asynchronous Convolutional Networks for Object Detection in Neuromorphic Camerascited by 57
  7. 2021Learning from Event Cameras with Sparse Spiking Convolutional Neural Networkscited by 25
  8. 2021Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Visioncited by 22
  9. 2020Low-activity supervised convolutional spiking neural networks applied to speech commands recognitioncited by 19
  10. 2019Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligencecited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 17; 2024: 27; 2025: 18; 2026: 15.

79 papers.

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  1. 2023SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligencecited by 163
  2. 2022Recurrent Vision Transformers for Object Detection with Event Camerascited by 158
  3. 2023SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networkscited by 82
  4. 2023Deep Directly-Trained Spiking Neural Networks for Object Detectioncited by 76
  5. 2024State Space Models for Event Camerascited by 75
  6. 2023GET: Group Event Transformer for Event-Based Visioncited by 73
  7. 2023From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detectioncited by 52
  8. 2024Scene Adaptive Sparse Transformer for Event-based Object Detectioncited by 39
  9. 2023Optical flow estimation from event-based cameras and spiking neural networkscited by 33
  10. 2022Pushing the Limits of Asynchronous Graph-based Object Detection with Event Camerascited by 32
  11. 2023Direct Learning-Based Deep Spiking Neural Networks: A Reviewcited by 31
  12. 2023LEOD: Label-Efficient Object Detection for Event Camerascited by 24
38 more
  1. 2024SFOD: Spiking Fusion Object Detectorcited by 19
  2. 2024EAS-SNN: End-to-End Adaptive Sampling and Representation for Event-based Detection with Recurrent Spiking Neural Networkscited by 16
  3. 2024Neuromorphic Drone Detection: an Event-RGB Multimodal Approachcited by 14
  4. 2025Event-based Tiny Object Detection: A Benchmark Dataset and Baselinecited by 14
  5. 2024SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Embedded AI Systemscited by 12
  6. 2023Spiking-Fer: Spiking Neural Network for Facial Expression Recognition With Event Camerascited by 10
  7. 2023To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Accelerationcited by 10
  8. 2024FlexEvent: Towards Flexible Event-Frame Object Detection at Varying Operational Frequenciescited by 10
  9. 2024A Recurrent YOLOv8-based framework for Event-Based Object Detectioncited by 9
  10. 2024EvRT-DETR: Latent Space Adaptation of Image Detectors for Event-based Visioncited by 9
  11. 2025Differential Coding for Training-Free ANN-to-SNN Conversioncited by 9
  12. 2024Spiking CenterNet: A Distillation-boosted Spiking Neural Network for Object Detectioncited by 8
  13. 2025Adaptive Event Stream Slicing for Open-Vocabulary Event-Based Object Detection via Vision-Language Knowledge Distillationcited by 8
  14. 2024EvSegSNN: Neuromorphic Semantic Segmentation for Event Datacited by 7
  15. 2024Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applicationscited by 7
  16. 2025Hybrid Spiking Vision Transformer for Object Detection with Event Camerascited by 7
  17. 2023SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networkscited by 6
  18. 2024ShapeAug: Occlusion Augmentation for Event Camera Datacited by 6
  19. 2023Automotive Object Detection via Learning Sparse Events by Spiking Neuronscited by 5
  20. 2024Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Visioncited by 5
  21. 2024Efficient Event-Based Object Detection: A Hybrid Neural Network with Spatial and Temporal Attentioncited by 5
  22. 2024MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognitioncited by 5
  23. 2025Event-Priori-Based Vision-Language Model for Efficient Visual Understandingcited by 5
  24. 2023NeuroCLIP: Neuromorphic Data Understanding by CLIP and SNNcited by 4
  25. 2024A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Datacited by 4
  26. 2024SNN4Agents: A Framework for Developing Energy-Efficient Embodied Spiking Neural Networks for Autonomous Agentscited by 4
  27. 2024Deep Event-based Object Detection in Autonomous Driving: A Surveycited by 4
  28. 2024SpikeBottleNet: Spike-Driven Feature Compression Architecture for Edge-Cloud Co-Inferencecited by 3
  29. 2025Spiking monocular event based 6D pose estimation for space applicationcited by 3
  30. 2025Event2Vec: Processing Neuromorphic Events Directly by Representations in Vector Spacecited by 3
  31. 2025Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detectioncited by 3
  32. 2023NU-AIR -- A Neuromorphic Urban Aerial Dataset for Detection and Localization of Pedestrians and Vehiclescited by 2
  33. 2024SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systemscited by 2
  34. 2024Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensorscited by 2
  35. 2024Embedded event based object detection with spiking neural networkcited by 2
  36. 2024Towards Efficient Deployment of Hybrid SNNs on Neuromorphic and Edge AI Hardwarecited by 2
  37. 2024Enabling Energy-Efficient Simultaneous Multi-Task Reinforcement Learning through Spiking Neural Networks with Active Dendrites for Bio-inspired Generalist Agentscited by 2
  38. 2025EvDetMAV: Generalized MAV Detection from Moving Event Camerascited by 2

50 most cited of 79 All 79 (JSON)