事件相机在昼夜光照差异下表现更稳定，减少域偏移影响。
Towards Closing the Domain Gap with Event Cameras
- 用事件相机替代传统摄像头应对光照变化带来的域偏移
- 在跨域场景中性能优于或不劣于灰度图像，且偏差更小
- 适合自动驾驶中需适应复杂光照的部署场景
尽管传统摄像头是端到端驾驶的主要传感器，其性能在训练数据与部署环境不匹配时显著下降，这种现象称为域偏移。本文聚焦昼夜光照差异导致的域偏移问题，提出以事件相机作为潜在替代方案，可在无需额外调整的情况下保持跨光照条件下的性能稳定。实验表明，事件相机在不同光照条件下表现出更一致的性能，其域偏移惩罚通常与灰度帧相当或更小，并在跨域场景中提供更优的基础性能。
原文摘要 · Abstract (English)
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.
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