Beyond the Snowflakes: Disentangling Weather Effects from Confounding Meta-Factors in LiDAR Object Detection

Paper recorded by Signals 4 on 2026-10-09 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12

Category: cs.CV · 计算机视觉 · first seen 2026-10-12

Abstract

Light Detection and Ranging (LiDAR) is critical for autonomous perception, yet its performance is known to degrade in adverse weather. While existing literature models snow as atmospheric noise that degrades performance, our granular evaluation on the WADS-3D and CADC datasets reveals a counter-intuitive phenomenon: detection accuracy consistently improves as snow intensity increases. Through abla

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