AI RESEARCH
CANDLE: Illumination-Invariant Semantic Priors for Color Ambient Lighting Normalization
arXiv CS.CV
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ArXi:2604.02785v1 Announce Type: new Color ambient lighting normalization under multi-colored illumination is challenging due to severe chromatic shifts, highlight saturation, and material-dependent reflectance. Existing geometric and low-level priors are insufficient for recovering object-intrinsic color when illumination-induced chromatic bias dominates. We observe that DINOv3's self-supervised features remain highly consistent between colored-light inputs and ambient-lit ground truth, motivating their use as illumination-robust semantic priors.