Motion estimation for region-based video coding
Why this work is in the frame
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Bibliographic record
Abstract
Region-based video compression has been a very active research area over the last few years. It has been viewed as a potential alternative to traditional schemes suffering from the "blockiness" of image intensities at very low bit rates. We present a new approach to region-based representation and motion estimation. It is based on the observation that motion boundaries usually coincide with region boundaries. Thus, we first compute an intensity-based image partition and use it as an initial step in a 3-step algorithm: motion estimation for intensity-derived regions, motion-based region fusion and adjustment of region boundaries. We present experimental results for standard QCIF images and compare our method with block matching and dense motion field estimation. We also study the performance loss due to a lossy transmission of partition information.
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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 | 0.001 |
| 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 | 0.001 | 0.003 |
| 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