Rate and Distortion Modeling of CGS Coded Scalable Video Content
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we derive single layer and scalable video rate and distortion models for video bitstreams encoded using the coarse grain quality scalability (CGS) feature of the scalable extension of H.264/AVC. In these models, we assume the source is Laplacian distributed and compensate for errors in the distribution assumption by linearly scaling the Laplacian parameter . Moreover, we present simplified approximations of the derived models that allow for a run-time calculation of sequence dependent model constants. Our models use the mean absolute difference (MAD) of the prediction residual signal and the encoder quantization parameter (QP) as input parameters. Consequently, we are able to estimate the residual MAD, bitrate, and distortion of a future video frame at any QP value and for both base-layer and CGS layer packets. We also present simulation results that demonstrate the accuracy of the proposed models.
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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 | 0.000 | 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