The human visual system's assumption that light comes from above is weak
Why this work is in the frame
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Bibliographic record
Abstract
Every biological or artificial visual system faces the problem that images are highly ambiguous, in the sense that every image depicts an infinite number of possible 3D arrangements of shapes, surface colors, and light sources. When estimating 3D shape from shading, the human visual system partly resolves this ambiguity by relying on the light-from-above prior, an assumption that light comes from overhead. However, light comes from overhead only on average, and most images contain visual information that contradicts the light-from-above prior, such as shadows indicating oblique lighting. How does the human visual system perceive 3D shape when there are contradictions between what it assumes and what it sees? Here we show that the visual system combines the light-from-above prior with visual lighting cues using an efficient statistical strategy that assigns a weight to the prior and to the cues and finds a maximum-likelihood lighting direction estimate that is a compromise between the two. The prior receives surprisingly little weight and can be overridden by lighting cues that are barely perceptible. Thus, the light-from-above prior plays a much more limited role in shape perception than previously thought, and instead human vision relies heavily on lighting cues to recover 3D shape. These findings also support the notion that the visual system efficiently integrates priors with cues to solve the difficult problem of recovering 3D shape from 2D images.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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