Complexity scalable video encoding for power-aware applications
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
Mobile multimedia application design has taken precedence in the field of wireless communications due to the growing demand for mobile devices to perform multimedia functions. To sustain such high complexity and power hungry functions on battery-powered devices, power-aware concepts should be employed in the design of mobile multimedia applications. An effective power-aware design should serve two functions. The first is to lower overall power consumption with minimum impact on performance and the second is to adjust its power consumption rate to extend the battery life of its platform. In this paper, we tackle one of the most up-and-coming multimedia functions, video compression, by introducing a novel complexity-scalable video encoding framework for power-aware applications. The proposed video encoder embodies both functions of power-aware design. The complexity-scalability is maintained efficiently through a single control-parameter; and significant complexity reduction rates are achieved through a novel prediction scheme. The performance of the proposed design is demonstrated and compared with some of the existing complexity reduction and complexity scalability techniques.
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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 | 0.002 | 0.001 |
| 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