Compressed domain spatial adaptation for H.264 video
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
In this paper, we present a metadata-based compressed-domain spatial adaptation scheme for H.264/AVC video. We have enhanced the H.264/AVC encoder with our proposed adaptation strategies in order to reduce video size by cropping individual frames in an intermediary node prior to transmitting that video to heterogeneous devices. In this regard, we exploit the sliced architecture of the video frames within the first version of the H.264/AVC specification and devise different slicing strategies. The compressed-domain bitstream modification is performed at the intermediary nodes, avoiding the need for any cascaded operations. Here, we briefly present our adaptation scheme as well as evaluation results showing the effectiveness of the slicing strategies on the bitrate reduction and processing time. A comparison of our approach with an existing cropping scheme is also presented.
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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