Improved skeleton extraction and surface generation for sketch-based modeling
Why this work is in the frame
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Bibliographic record
Abstract
Figure 1: Surface Generation (from left to right): sketched silhouette, extracted skeleton and internal edges, sketched profile curve and resulting model. For the generation of freeform models, sketching interfaces have raised an increasing interest due to their intuitive approach. It is now possible to infer a 3D model directly from a sketched curved. Unfortunately, a limit of current systems is the poor quality of the skeleton automatically extracted from this silhouette, leading to low quality meshes for the resulting objects. In this paper, we present new solutions that improve the surface generation for sketch-based modeling systems. First, we propose a new algorithm that extracts a smoother skeleton compared to previous approaches. Then, we present a new sampling scheme for the creation of good-quality 3D mesh. Finally, we propose to use a profile curve composed of disconnected components in order to create models which genus is greater than 0.
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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 | 0.001 |
| Open science | 0.000 | 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