Diverse Bases for Functional Spaces for Non-Rigid Shape Correspondence
Why this work is in the frame
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Bibliographic record
Abstract
Computing meaningful correspondences for shapes undergoing non-rigid deformations is a fundamental task, challenging shape analysis community for many decades.The functional map framework has emerged as a powerful tool in this domain over the past decade due to its computational efficiency.Instead of tackling the combinatorial challenge of matching individual points across shapes, it focuses on constructing a linear mapping between the spaces of functions defined on these shapes.The map between function spaces is specified by a low-dimensional matrix obtained via suitably chosen basis functions that characterize the function space.This mapping can then be converted into a point-to-point correspondence between the shapes.The selection of an appropriate basis is a critical factor influencing the overall effectiveness and precision of the task.This survey explores various bases proposed to represent function spaces comprehensively within the realm of shape correspondence.Further insights into possible future directions are also provided.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.006 | 0.026 |
| Open science | 0.001 | 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