Low-Delay Hevc Adaptive Quantization Parameter Selection through Temporal Propagation Length Estimation
Bibliographic record
Abstract
Rate Distortion Optimization (RDO) is employed in the contemporary video coding standard, High Efficiency Video Coding (HEVC), to improve its coding efficiency. Due to its high complexity, RDO is generally performed with fixed quantization parameters (QPs). Fixing QPs, however, does not consider the impact of the current frame on the future frames within the temporal propagation chain, leading to suboptimal performance. To address the adaptive QP design, in this paper, we first estimate the propagation length that is defined as the impact length of the current unit on future units. Based on this impact length, we then propose an adaptive frame-level QP selection algorithm for the low-delay (LD) HEVC standard. Compared to the default HEVC, our method performs significantly better by achieving -4.71% and -3.93% BD-rate gains for LDP and LDB configurations of HEVC, respectively, at a negligible increase in time overhead.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".