mlsanityData to 7 Oct 2026

A Recurrent YOLOv8-based framework for Event-Based Object Detection

arXiv 2408.05321 ↗First posted 9 Aug 2024cs.CV cs.AIcited by 9

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Abstract (arXiv)

Object detection is crucial in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on data from conventional frame-based RGB sensors. However, these sensors often struggle with issues like motion blur and poor performance in challenging lighting conditions. In response to these challenges, event-based cameras have emerged as an innovative paradigm. These cameras, mimicking the human eye, demonstrate superior performance in environments with fast motion and extreme lighting conditions while consuming less power. This study introduces ReYOLOv8, an advanced object detection framework that enhances a leading frame-based detection system with spatiotemporal modeling capabilities. We implemented a low-latency, memory-efficient method for encoding event data to boost the system's performance. We also developed a novel data augmentation technique tailored to leverage the unique attributes of event data, thus improving detection accuracy. Our models outperformed all comparable approaches in the GEN1 dataset, focusing on automotive applications, achieving mean Average Precision (mAP) improvements of 5%, 2.8%, and 2.5% across nano, small, and medium scales, respectively.These enhancements were achieved while reducing the number of trainable parameters by an average of 4.43% and maintaining real-time processing speeds between 9.2ms and 15.5ms. On the PEDRo dataset, which targets robotics applications, our models showed mAP improvements ranging from 9% to 18%, with 14.5x and 3.8x smaller models and an average speed enhancement of 1.67x.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 52 of its 85 references that are in the map. First posted on arXiv 9 Aug 2024.

Builds on

52 of 85 references.

References · 52

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38 more
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  9. 2019End-to-End Learning of Representations for Asynchronous Event-Based Datacited by 216
  10. 2018HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classificationcited by 215
  11. 2018Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Carscited by 197
  12. 2020Learning to Detect Objects with a 1 Megapixel Event Cameracited by 184
  13. 2022Recurrent Vision Transformers for Object Detection with Event Camerascited by 158
  14. 2023A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAScited by 149
  15. 2022AEGNN: Asynchronous Event-based Graph Neural Networkscited by 118
  16. 2020A Large Scale Event-based Detection Dataset for Automotivecited by 108
  17. 2020Event-based Asynchronous Sparse Convolutional Networkscited by 103
  18. 2019Graph-Based Object Classification for Neuromorphic Vision Sensingcited by 85
  19. 2022Object Detection with Spiking Neural Networks on Automotive Event Datacited by 79
  20. 2023Deep Directly-Trained Spiking Neural Networks for Object Detectioncited by 76
  21. 2024State Space Models for Event Camerascited by 75
  22. 2021Time-Ordered Recent Event (TORE) Volumes for Event Camerascited by 73
  23. 2023GET: Group Event Transformer for Event-Based Visioncited by 73
  24. 2022Neuromorphic Data Augmentation for Training Spiking Neural Networkscited by 52
  25. 2023From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detectioncited by 52
  26. 2023Hierarchical Neural Memory Network for Low Latency Event Processingcited by 45
  27. 2024Scene Adaptive Sparse Transformer for Event-based Object Detectioncited by 39
  28. 2021EventDrop: data augmentation for event-based learningcited by 28
  29. 2023LEOD: Label-Efficient Object Detection for Event Camerascited by 24
  30. 2022Motion Robust High-Speed Light-Weighted Object Detection With Event Cameracited by 23
  31. 2021Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Visioncited by 22
  32. 2020Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Camerascited by 19
  33. 2024SFOD: Spiking Fusion Object Detectorcited by 19
  34. 2022Are High-Resolution Event Cameras Really Needed?cited by 18
  35. 2023Dual Memory Aggregation Network for Event-Based Object Detection with Learnable Representationcited by 16
  36. 2024EAS-SNN: End-to-End Adaptive Sampling and Representation for Event-based Detection with Recurrent Spiking Neural Networkscited by 16
  37. 2024EventRPG: Event Data Augmentation with Relevance Propagation Guidancecited by 7
  38. 2024ShapeAug: Occlusion Augmentation for Event Camera Datacited by 6

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 6.

9 papers.

  1. 2025Beyond Domain Randomization: Event-Inspired Perception for Visually Robust Adversarial Imitation from Videoscited by 1
  2. 2026Efficient Multi-Timescale Event Representations for Feed-Forward Object Detectioncited by 1
  3. 2024Chimera: A Block-Based Neural Architecture Search Framework for Event-Based Object Detectioncited by 0
  4. 2025CETUS: Causal Event-Driven Temporal Modeling With Unified Variable-Rate Schedulingcited by 0
  5. 2026Sensor Generalization for Adaptive Sensing in Event-based Object Detection via Joint Distribution Trainingcited by 0
  6. 2026Benchmarking Recurrent Event-Based Object Detection for Industrial Multi-Class Recognition on MTeventcited by 0
  7. 2026NERVE: A Neuromorphic Vision and Radar Ensemble for Multi-Sensor Fusion Researchcited by 0
  8. 2026Brain-inspired spike-timing plasticity for reliable label-efficient event-camera visioncited by 0
  9. 2026Neuromorphic Object Detection: An In-Depth Study and Future Directionscited by 0