Confidence interval based motion estimation
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
A new video standard called High Efficiency Video Coding (HEVC) is now being finalized. In comparison with the H.264/AVC video coding standard, HEVC further improves video coding rate distortion (RD) performance, but at the price of significant increase in its encoding complexity, especially in its motion estimation (ME). To reduce the ME complexity in HEVC while maintaining its RD performance, in this paper, we first formulate ME as a statistical inference problem and then propose a confidence interval based ME method. It is shown by experiments that, for the four test sequences with higher searching complexity under low delay main, our proposed ME method further reduces the integer level ME time of the fast search in HEVC by 73.49% on average with only 1.22% increase in bit rate and 0.024dB loss in PSNR.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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