mlsanityData to 14 Oct 2026

Sensor Generalization for Adaptive Sensing in Event-based Object Detection via Joint Distribution Training

arXiv 2602.23357 ↗First posted 26 Feb 2026cs.CVcited by 0

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Abstract (arXiv)

Bio-inspired event cameras have recently attracted significant research due to their asynchronous and low-latency capabilities. These features provide a high dynamic range and significantly reduce motion blur. However, because of the novelty in the nature of their output signals, there is a gap in the variability of available data and a lack of extensive analysis of the parameters characterizing their signals. This paper addresses these issues by providing readers with an in-depth understanding of how intrinsic parameters affect the performance of a model trained on event data, specifically for object detection. We also use our findings to expand the capabilities of the downstream model towards sensor-agnostic robustness.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 32 of its 45 references that are in the map. First posted on arXiv 26 Feb 2026.

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32 of 45 references.

References · 32

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
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  3. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,071
  4. 2021Generalizing to Unseen Domains: A Survey on Domain Generalizationcited by 766
  5. 2021Domain Generalization: A Surveycited by 764
  6. 2018HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classificationcited by 218
  7. 2018Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Carscited by 200
  8. 2020Learning to Detect Objects with a 1 Megapixel Event Cameracited by 186
  9. 2019Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detectioncited by 177
  10. 2019Video to Events: Recycling Video Datasets for Event Camerascited by 165
  11. 2022Recurrent Vision Transformers for Object Detection with Event Camerascited by 159
  12. 2021Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networkscited by 139
20 more
  1. 2022AEGNN: Asynchronous Event-based Graph Neural Networkscited by 118
  2. 2020A Large Scale Event-based Detection Dataset for Automotivecited by 109
  3. 2021Temporal-wise Attention Spiking Neural Networks for Event Streams Classificationcited by 106
  4. 2019Graph-Based Object Classification for Neuromorphic Vision Sensingcited by 85
  5. 2022Object Detection with Spiking Neural Networks on Automotive Event Datacited by 80
  6. 2023Deep Directly-Trained Spiking Neural Networks for Object Detectioncited by 77
  7. 2024State Space Models for Event Camerascited by 75
  8. 2021Time-Ordered Recent Event (TORE) Volumes for Event Camerascited by 73
  9. 2023GET: Group Event Transformer for Event-Based Visioncited by 73
  10. 2023Hierarchical Neural Memory Network for Low Latency Event Processingcited by 47
  11. 2022Optimized Potential Initialization for Low-latency Spiking Neural Networkscited by 41
  12. 2022Pushing the Limits of Asynchronous Graph-based Object Detection with Event Camerascited by 32
  13. 2023Direct Learning-Based Deep Spiking Neural Networks: A Reviewcited by 31
  14. 2022Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikescited by 30
  15. 2024SFOD: Spiking Fusion Object Detectorcited by 20
  16. 2021DA4Event: towards bridging the Sim-to-Real Gap for Event Cameras using Domain Adaptationcited by 14
  17. 2023Unsupervised Domain Adaptation for Training Event-Based Networks Using Contrastive Learning and Uncorrelated Conditioningcited by 14
  18. 2024A Recurrent YOLOv8-based framework for Event-Based Object Detectioncited by 9
  19. 2024Generalized Event Camerascited by 7
  20. 2024Frequency-Adaptive Low-Latency Object Detection Using Events and Framescited by 7

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