Video Quality Metric for Bit Rate Control via Joint Adjustment of Quantization and Frame Rate
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
The purpose of this study is to propose a quality metric of video encoded with variable frame rates and quantization parameters suitable for mobile video broadcasting applications. As a first step, experiments are conducted to assess the subjective quality of video sequences encoded with variable frame rates and quantization parameters. Resulting experimental data show that for the purpose of video rate control, optimization using the classical PSNR does not match up to that of subjective quality data. The second step bridges this gap between PSNR and subjective quality data by constructing a new quality metric that accounts for both encoding parameters (quantization and frame rate), and intrinsic video sequence characteristics (motion speed). The average correlation coefficient for five video sequences tested is as high as 0.93 with the proposed metric, in contrast with the PSNR's 0.70
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 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