Motion vector prediction for improving one bit transform 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
One bit transforms (1BT) have been proposed for lowering the complexity of motion estimation (ME) in video coding. These transforms generate a one bit representation of each pixel in the video that is used in the motion search. This approach can greatly reduce the silicon area and power required for hardware based video encoding. However 1BT methods under-perform traditional Sum of absolute differences (SAD) based motion estimation, particularly for smaller block sizes. In this paper, it is proposed to improve 1BT based ME by predicting the motion vector for each block based on the vectors from previous blocks and modifying the cost function to favor motion vectors close to the predicted one. This takes advantage of the spatial correlation between motion vectors and produces a more uniform motion field. Simulation results show the proposed method can improve the PSNR of frames reconstructed through motion compensation by up to 1 dB and substantially improve the subjective video quality by reducing blocking 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 | 0.001 |
| 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