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Record W176198518

3D-TV: coding of disocclusions for 2D+depth representation of multi-view images

2008· article· en· W176198518 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVideo Coding and Compression Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsView synthesisPixelComputer scienceComputer visionEmbeddingRendering (computer graphics)Artificial intelligenceCoding (social sciences)ENCODEWaveletExploitComputer graphics (images)Depth mapMathematicsImage (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.764
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.336
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it