White Patch Gamut Mapping Colour Constancy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The White-Patch method, one of the first colour constancy methods, estimates the light source colour from the maximum response of the different colour channels. However, it has been eclipsed by the advent of more advanced physical or statistical methods, as well as complex learning based methods. Recently, a new independent line of work claims that the simple idea of using maximum pixel values is not as naive as it seems, but can also be made to perform very well via some manipulations. The bright areas of images can include highlights and specularity as well as white surfaces or light sources, and indeed all may be helpful in the illumination estimation process. In this paper, we define the White Patch Gamut as a new extension to the Gamut Mapping Colour Constancy method, comprising the bright pixels of the image. Adding new constraints based on the possible White Patch Gamut to the standard gamut mapping constraints, a new combined method outperforms gamut mapping methods as well as other wellknown colour constancy methods. The new constraints that are brought to bear are powerful, and indeed can be more discriminating than those in the original gamut mapping method itself.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it