3D-TV: coding of disocclusions for 2D+depth representation of multi-view images
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
The 2D+depth (2D+D) format has recently emerged as a good candidate for the transmission of multi-view content in a 3D-TV broadcasting environment because it allows the rendering of new views with minimum processing requirements. Its main drawback is the appearance of disoccluded areas in the rendered views. We explore a way to encode these disoccluded areas as an enhancement layer in a 2D+D representation. We exploit the fact that the disocclusion is generally an extension to the farther side in a depth edge. We used an interpolating wavelet decomposition of the horizontal line formed by embedding the disoccluded area between the pixels defining the depth edge. This strategy preserves the value of pixels in the transmitted view. Our results show that the proposed method reduces the amount of information needed if compared to the simultaneous transmission of all views while improving the quality of the new views rendered from the 2D+D representation.
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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