Coding unit splitting early termination for fast HEVC intra coding based on global and directional gradients
Why this work is in the frame
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Bibliographic record
Abstract
High efficiency video coding (HEVC) doubles the compression ratio as compared to H.264/AVC, for the same quality. To achieve this improved coding performance, HEVC presents a new content-adaptive approach to split a frame into coding units (CUs), along with an increased number of prediction modes, which results in significant computational complexity. To lower this complexity with intra coding, in this paper, we develop a new method based on global and directional gradients to terminate the CU splitting procedure early and prevent processing of unnecessary depths. The global and directional gradients determine if the unit is predicted with high accuracy at the current level, and where that's the case, the CU is deemed to be non-split. Experimental results show that the proposed method reduces the encoding time by 52% on average, with a small quality loss of 0.07 dB (BD-PSNR) for all-intra scenarios, as compared to the HEVC reference implementation, HM 15.0.
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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