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Record W3081508396 · doi:10.1117/12.2569246

MPEG-5 part 2: Low Complexity Enhancement Video Coding (LCEVC): Overview and performance evaluation

2020· article· en· W3081508396 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 institutionsUniversity of Manitoba
Fundersnot available
KeywordsCodecComputer scienceAdaptive Multi-Rate audio codecCoding (social sciences)Multiview Video CodingData compressionScalable Video CodingVideo compression picture typesStandardizationContext-adaptive binary arithmetic codingVideo processingMotion compensationComputer hardwareComputer visionVideo trackingMathematics

Abstract

fetched live from OpenAlex

Low Complexity Enhancement Video Coding (LCEVC) is a new MPEG video codec, currently undergoing standardization as MPEG-5 Part 2. Rather than being another video codec, LCEVC enhances any other codec (e.g. AVC, VP9, HEVC, AV1, EVC or VVC) to produce a reduced computational load and a compression efficiency higher than what is achievable by the enhanced codec used alone for a given resolution, especially at video delivery relevant bitrates. The core idea is to use a conventional video codec as a base codec at a lower resolution and reconstruct a full resolution video by combining the decoded low-resolution video with up to two enhancement sub-layers of residuals encoded with specialized low-complexity coding tools.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.462

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 science0.0010.001
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 head0.152
GPT teacher head0.308
Teacher spread0.157 · 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

Quick stats

Citations23
Published2020
Admission routes1
Has abstractyes

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