AMVP candidate list construction with zero motion vector for beyond VVC

Completing standardization of the VVC in July 2020, the Joint Video Experts Team of ISO/IEC SC29/WG05 launched the "Beyond VVC" exploration by developing the Enhanced Compression Model (ECM) which keeps integrating newly developed advanced encoding tools together. In inter prediction, the Advanced Motion Vector Prediction (AMVP) method encodes motion vectors using Motion Vector Predictor (MVP) selected from MVP candidate list. In the current ECM of version 11.0, unless zero MV is added at the first place into the candidate list while at least one neighboring block has zero MV, zero MV has very low probability to be selected as MVP, thus potentially resulting in reduced coding efficiency. To overcome this limitation, we investigate a method that puts zero MV into the list unless the list is already full so that the zero MV can be subject to MVP refinement and reordering process to improve coding efficiency. Experimental results demonstrate BDBR gain of 0.03% in the luma channel.

Authors

Institutions

Publication Details

Published
2025-02-05
DOI
https://doi.org/10.1117/12.3058064
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AMVP candidate list construction with zero motion vector for beyond VVC

Byeungwoo Jeon, Seori Park
Advanced Vision and Imaging
article

AMVP candidate list construction with zero motion vector for beyond VVC

Byeungwoo Jeon, Seori Park
article en

Abstract

Completing standardization of the VVC in July 2020, the Joint Video Experts Team of ISO/IEC SC29/WG05 launched the "Beyond VVC" exploration by developing the Enhanced Compression Model (ECM) which keeps integrating newly developed advanced encoding tools together. In inter prediction, the Advanced Motion Vector Prediction (AMVP) method encodes motion vectors using Motion Vector Predictor (MVP) selected from MVP candidate list. In the current ECM of version 11.0, unless zero MV is added at the first place into the candidate list while at least one neighboring block has zero MV, zero MV has very low probability to be selected as MVP, thus potentially resulting in reduced coding efficiency. To overcome this limitation, we investigate a method that puts zero MV into the list unless the list is already full so that the zero MV can be subject to MVP refinement and reordering process to improve coding efficiency. Experimental results demonstrate BDBR gain of 0.03% in the luma channel.

Sungkyunkwan University (KR)
Openalex Percentile: Top 99%
Advanced Vision and Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.