Trailing artifact avoidance for low bit-rate block-based video coders
Why this work is in the frame
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Bibliographic record
Abstract
A method is provided to avoid or otherwise reduce luminance and/or chrominance trailing artifacts in block-based hybrid video coders. The proposed trailing artifact avoidance approach has at its core three main components. The first component is a method to identify flat blocks in the source frame where the appearance of trailing artifacts would be very noticeable, and where flatness is determined according to several proposed criteria. The second component is a method to identify bad blocks, which refer to predicted blocks in motion estimation that correspond to flat blocks in the source frame and that contain trailing artifacts. The third component is a high performance motion estimation approach to avoid trailing artifacts when they are detected within a bad block. Experimental results using an H.264 based-coder indicate the proposed method is very effective in reducing or eliminating the appearance of trailing artifacts.
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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