Fast inter mode decision for HEVC based on transparent composite model
Why this work is in the frame
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Bibliographic record
Abstract
In comparison with H.264/AVC, the newest video coding standard, High Efficiency Video Coding (HEVC), improves video coding rate distortion (RD) performance, but at the price of significant increase in its encoding complexity, due to its complicated inter mode decision process. In HEVC inter coding, the actual RD costs of all combinations of coding units (CUs), prediction units (PUs), and transform units (TUs) have to be computed and then the combination (i.e., mode) with the minimum cost is selected and encoded. To reduce the inter mode decision complexity in HEVC while maintaining its coding efficiency, in this paper, a fast inter mode decision method based on a newly proposed Transparent Composite Model (TCM) is developed. Spatially and temporally homogeneities are identified by TCM, and then used, together with spatiotemporal correlation between CUs, to determine PU and CU partitions so that cost computations of unnecessary modes can be skipped. Experimental results show that, for the low delay main test configuration of HEVC, our method reduces, on average, the encoding time by 60.71% with an insignificant loss in coding efficiency (1.06% BD-Rate increase).
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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