Solid-Shell Labeling for Discrete Surfaces
Bibliographic record
Abstract
Artist-created meshes in-the-wild often do not have a well defined interior. We observe that they typically consist of a mix of solid elements, faces that bound a volume, and shell elements that represent the medial surface of a thin shell. The lack of a well-defined interior prevents downstream applications, such as solid-modeling, simulation, and manufacturing. We present a method that takes as input a surface mesh and assigns to each face a label determining whether it belongs to a solid or shell. These labels reduce ambiguity by defining the interior for solid faces through thresholding the generalized winding number field, and for shell faces as the volume within an offset. We cast the labeling problem as an optimization that outputs a solid/shell label for each face, guided by a sparse set of user inputs. Once labeling is complete, we show how the shape can be volume meshed by passing the shell faces through an offset mesher and the solid faces to an off-the-shelf tetrahedral mesher, producing a final volumetric mesh by taking their union. Experiments on diverse meshes with defects and multiple solid and shell components demonstrate that our approach delivers the desired labels, enabling modeling and simulation on wild meshes in a way that respects the user intent.
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How this classification was reachedexpand
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) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".