A Perceptually Driven Model for Transmission of Arbitrary 3D Models over Unreliable Networks
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
3D transmission over unreliable networks needs to take into account the possibility of packet loss. In this work we describe a perceptually motivated strategy for joint transmission of texture and mesh over unreliable networks. The approach is described initially considering regular mesh structure, to show the utility of optimizing the texture-mesh tradeoff. In order to generalize our approach to arbitrary meshes we consider stripification of the mesh, combined with a strategy that does not need texture or vertex packets to be re-transmitted. Only the valence (connectivity) packets need to be re-transmitted; however, storage of valence information requires only 10% space compared to vertices and even less compared to photo-realistic texture. Thus, only less than 5% of the packets may need to be re-transmitted in the worst case to allow our algorithm to successfully reconstruct an acceptable object under severe packet loss. Results showing the implementation of the proposed approach are described.
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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 | 0.000 |
| 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