Exploring the Space of Human Body Shapes: Data-driven Synthesis under Anthropometric Control
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<div class="htmlview paragraph">In this paper, we demonstrate a system for synthesizing high-resolution, realistic 3D human body shapes according to user-specified anthropometric parameters. We begin with a corpus of whole-body 3D laser range scans of 250 different people. For each scan, we warp a common template mesh to fit each scanned shape, thereby creating a one-to-one vertex correspondence between each of the example body shapes. Once we have a common surface representation for each example, we then use principal component analysis to reduce the data storage requirements. The final step is to relate the variation of body shape with concrete parameters, such as body circumferences, point-to-point measurements, etc. These parameters can then be used as “sliders” to synthesize new individuals with the required attributes, or to edit the attributes of scanned individuals.</div>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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