Context Similarity-Enabled CU Partitioning Algorithm in VVC
Bibliographic record
Abstract
A new Quadtree with nested multi-type tree(QTMT) partitioning method is adopted in the latest video coding standard Versatile Video Coding(VVC) to achieve effective encoding. Compared with Quadtree(QT) in HEVC, QTMT can provide enhanced encoding performance. However, this improved coding performance is obtained at the cost of additional computational load from recursive and nested searches for the best CU structure. A context similarity-enabled CU partitioning algorithm is proposed to achieve a balance between coding efficiency and compression quality in VVC. According to the difference between frames, the method of frame difference algorithm is used to calculate the possibility that the current block can follow the same subblock division mode of the previous frame, so as to skip the unnecessary division selection process. The experimental results show that the proposed method can save the encoding time up to 18.22% with about 0.91% BD-rate degradation on average compared with VVC software reference VTM-9.3
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".