Perceptually-friendly rate distortion optimization in high efficiency video coding
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
We propose the employment of a perceptual video quality metric in measuring the distortion in the High Efficiency Video Coding (HEVC) Standard. The mean square error presently used as quality metric is not a good measure to use, as it poorly correlates with human perception. Integration of a video quality metric based on the characteristics of the Human Visual System (HVS) inside the rate distortion optimization procedure is expected to improve the compression efficiency of the video coding. In this paper, the PSNR-HVS measure is used in the rate distortion optimization process. The compression efficiency of the proposed approach is compared to that used by HEVC, the recent video coding standard. Simulations prove that the proposed approach yields higher compression efficiency and provides better visual quality.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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