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paperarXivTrust 82 · PrimaryPublished yesterdayLive · 6h ago

Cyclone: Diffusion Model for Cycle-Consistent Weather Editing from Unpaired Driving Data

Reliable perception under diverse weather conditions remains a major challenge for autonomous driving systems. A common strategy to improve robustness is either to synthesize adverse weather conditions for training perception models or to apply weather-removal techniques to recover clean inputs. However, existing approaches typically rely on synthetic data augmentation or physics-based, task-specific models that require paired training data and often struggle to generate realistic weather effects or generalize robustly to out-of-domain scenarios. Toward this problem, we present Cyclone, a unif

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