CANDLE: Illumination-Invariant Semantic Priors for Color Ambient Lighting Normalization
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. We propose CANDLE (Color Ambient Normalization with DINO Layer Enhancement), which introduces DINO Omni-layer Guidance (D.O.G.) to adaptively inject multi-layer DINOv3 features int...
| Authors | Rong-Lin Jian, Ting-Yao Chen, Yu-Fan Lin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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