Isosurface Ambient Occlusion and Soft Shadows with Filterable Occlusion Maps
Why this work is in the frame
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Bibliographic record
Abstract
Volumetric data sets are often examined by displaying isosurfaces, surfaces where the data or function takes on a given value. We propose a new method for rendering isosurfaces at interactive rates while supporting dynamic ambient occlusion and/or soft shadows and requiring minimal pre-computation time. By approximating the occlusion in a region as the percentage of occluding voxels in that region, we reduce the ambient occlusion problem to the same problem faced in soft shadow mapping algorithms. In order to quickly extract the number of occluding voxels in an image region, we propose representing distributions using filterable representations such as variance shadow maps or convolution shadow maps. By choosing different sampling patterns from these maps we can dynamically approximate ambient occlusion and/or soft shadows.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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