mlsanityData to 7 Oct 2026

Towards Closing the Domain Gap with Event Cameras

arXiv 2512.16178 ↗First posted 18 Dec 2025cs.CV cs.AI cs.ROcited by 0

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Abstract (arXiv)

Although traditional cameras are the primary sensor for end-to-end driving, their performance suffers greatly when the conditions of the data they were trained on does not match the deployment environment, a problem known as the domain gap. In this work, we consider the day-night lighting difference domain gap. Instead of traditional cameras we propose event cameras as a potential alternative which can maintain performance across lighting condition domain gaps without requiring additional adjustments. Our results show that event cameras maintain more consistent performance across lighting conditions, exhibiting domain-shift penalties that are generally comparable to or smaller than grayscale frames and provide superior baseline performance in cross-domain scenarios.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 28 references that are in the map. First posted on arXiv 18 Dec 2025.

Builds on

14 of 28 references.

References · 14

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016End to End Learning for Self-Driving Carscited by 1,000
  3. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  4. 2019Exploring the Limitations of Behavior Cloning for Autonomous Drivingcited by 343
  5. 2022Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baselinecited by 247
  6. 2018Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Carscited by 197
  7. 2021End-to-End Urban Driving by Imitating a Reinforcement Learning Coachcited by 191
  8. 2018Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttimecited by 122
  9. 2023Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Surveycited by 101
  10. 2020DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Predictioncited by 56
  11. 2024Seeing Motion at Nighttime with an Event Cameracited by 33
  12. 2019See Clearer at Night: Towards Robust Nighttime Semantic Segmentation through Day-Night Image Conversioncited by 30
2 more
  1. 2023Chasing Day and Night: Towards Robust and Efficient All-Day Object Detection Guided by an Event Cameracited by 21
  2. 2016Steering a Predator Robot using a Mixed Frame/Event-Driven Convolutional Neural Networkcited by 15

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  1. 2026EventDrive: Event Cameras for Vision-Language Driving Intelligence
  2. 2023Towards Anytime Optical Flow Estimation with Event Cameras
  3. 2026SUV: Future Scene Understanding as Video Generation for End-to-End Driving
  4. 2024An Event-Oriented Diffusion-Refinement Method for Sparse Events Completion
  5. 2026Energy-Aware Imitation Learning for Steering Prediction Using Events and Frames
  6. 2024Revisiting RGBT Tracking Benchmarks from the Perspective of Modality Validity: A New Benchmark, Problem, and Solution
  7. 2024Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving
  8. 2026A Degradation-Tolerance Benchmark for Camera-Only End-to-End Driving