mlsanityData to 14 Oct 2026

EventSSEG: Event-driven Self-Supervised Segmentation with Probabilistic Attention

arXiv 2508.14856 ↗First posted 20 Aug 2025cs.CVcited by 0

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Abstract (arXiv)

Road segmentation is pivotal for autonomous vehicles, yet achieving low latency and low compute solutions using frame based cameras remains a challenge. Event cameras offer a promising alternative. To leverage their low power sensing, we introduce EventSSEG, a method for road segmentation that uses event only computing and a probabilistic attention mechanism. Event only computing poses a challenge in transferring pretrained weights from the conventional camera domain, requiring abundant labeled data, which is scarce. To overcome this, EventSSEG employs event-based self supervised learning, eliminating the need for extensive labeled data. Experiments on DSEC-Semantic and DDD17 show that EventSSEG achieves state of the art performance with minimal labeled events. This approach maximizes event cameras capabilities and addresses the lack of labeled events.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 28 of its 36 references that are in the map. First posted on arXiv 20 Aug 2025.

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28 of 36 references.

References · 28

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16 more
  1. 2019Event-based Vision: A Surveycited by 1,016
  2. 2021ResNet strikes back: An improved training procedure in timmcited by 368
  3. 2019High Speed and High Dynamic Range Video with an Event Cameracited by 345
  4. 2018EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Camerascited by 224
  5. 2020Hierarchical Multi-Scale Attention for Semantic Segmentationcited by 183
  6. 2019Video to Events: Recycling Video Datasets for Event Camerascited by 165
  7. 2020Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancycited by 125
  8. 2018EV-SegNet: Semantic Segmentation for Event-based Camerascited by 93
  9. 2022ESS: Learning Event-based Semantic Segmentation from Still Imagescited by 82
  10. 2021EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillationcited by 47
  11. 2023Hierarchical Neural Memory Network for Low Latency Event Processingcited by 47
  12. 2020ISSAFE: Improving Semantic Segmentation in Accidents by Fusing Event-based Datacited by 42
  13. 2022Masked Event Modeling: Self-Supervised Pretraining for Event Camerascited by 41
  14. 2024OpenESS: Event-based Semantic Scene Understanding with Open Vocabulariescited by 38
  15. 2021Improving Transformers with Probabilistic Attention Keyscited by 28
  16. 2024Exploiting Low-level Representations for Ultra-Fast Road Segmentationcited by 4

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