OmniLight is a generalized WD-MoE model for shadow removal and adverse lighting normalization that, along with a specialized baseline, achieved top rankings in all NTIRE 2026 Challenge lighting tracks.
Regional atten- tion for shadow removal
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A three-stage progressive refinement model guided by DINOv2 semantics and geometric depth/normals cues won the NTIRE 2026 image shadow removal challenge with top scores of 26.68 PSNR and 0.874 SSIM.
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OmniLight: One Model to Rule All Lighting Conditions
OmniLight is a generalized WD-MoE model for shadow removal and adverse lighting normalization that, along with a specialized baseline, achieved top rankings in all NTIRE 2026 Challenge lighting tracks.
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Winner of CVPR2026 NTIRE Challenge on Image Shadow Removal: Semantic and Geometric Guidance for Shadow Removal via Cascaded Refinement
A three-stage progressive refinement model guided by DINOv2 semantics and geometric depth/normals cues won the NTIRE 2026 image shadow removal challenge with top scores of 26.68 PSNR and 0.874 SSIM.