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Driving behavior recognition via self-discovery learning

arXiv 2503.14194 ↗First posted 18 Mar 2025cs.AIcited by 0

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Abstract (arXiv)

Autonomous driving systems require a deep understanding of human driving behaviors to achieve higher intelligence and safety.Despite advancements in deep learning, challenges such as long-tail distribution due to scarce samples and confusion from similar behaviors hinder effective driving behavior detection.Existing methods often fail to address sample confusion adequately, as datasets frequently contain ambiguous samples that obscure unique semantic information.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 20 of its 30 references that are in the map. First posted on arXiv 18 Mar 2025.

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20 of 30 references.

References · 20

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
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  11. 2022SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Drivingcited by 32
  12. 2022GateHUB: Gated History Unit with Background Suppression for Online Action Detectioncited by 27
8 more
  1. 2022RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-trainingcited by 25
  2. 2022Colar: Effective and Efficient Online Action Detection by Consulting Exemplarscited by 21
  3. 2020When Dictionary Learning Meets Deep Learning: Deep Dictionary Learning and Coding Network for Image Recognition with Limited Datacited by 11
  4. 2019Label Embedded Dictionary Learning for Image Classificationcited by 8
  5. 2023Ego-Vehicle Action Recognition based on Semi-Supervised Contrastive Learningcited by 8
  6. 2023E2E-LOAD: End-to-End Long-form Online Action Detectioncited by 8
  7. 2022A Circular Window-based Cascade Transformer for Online Action Detectioncited by 4
  8. 2018Semi-supervised Learning: Fusion of Self-supervised, Supervised Learning, and Multimodal Cues for Tactical Driver Behavior Detectioncited by 3

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