AI Paper Atlas

Research map / Image generation / Image restoration

Radiometric Calibration From Faces in Images

CVPR 2017 · Image generation › Image restoration · approach: Image harmonization and color transformation · 10 citations (OpenAlex)

Check your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use skin pigment low-rank calibration with geometry-guided shading decomposition instead of the strongest baseline, ISCRFSingle-image radiometric calibration · Synthetic images (DoRF)RMSE (×102): 21.9 -> 3.70Helped
Use skin pigment low-rank calibration with geometry-guided shading decomposition instead of the strongest baseline, ISCRFSingle-image radiometric calibration · Real imagesRMSE (×102): 9.18 -> 3.45Helped
Add geometry-guided intrinsic image decomposition to account for shading variation (ablation)Skin pigment calibration · Synthetic images (DoRF)RMSE (×102): 12.5 -> 3.70Helped
Add geometry-guided intrinsic image decomposition to account for shading variation (ablation)Skin pigment calibration · Real imagesRMSE (×102): 5.65 -> 3.45Helped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy