AI RESEARCH
Enhancing Event-based Object Detection with Monocular Normal Maps
arXiv CS.CV
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ArXi:2508.02127v2 Announce Type: replace Object detection in autonomous driving is frequently compromised by complex illumination. While event cameras offer a robust solution, they are susceptible to sudden contrast changes such as reflections which often trigger dense, misleading event signals. To overcome this, we leverage RGB-derived surface normal maps as explicit geometric constraints. Crucially, even when RGB degrades, they preserve low-frequency structural priors that effectively assist in event-based detection.