Skip to main navigation Skip to search Skip to main content

Rate Adaptation for Learned Two-layer B-frame Coding without Signaling Motion Information

Hong Sheng Xie*, Yi Hsin Chen, Wen Hsiao Peng, Martin Benjak, Jorn Ostermann

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Abstract

This paper explores the potential of a learned two-layer B-frame codec, known as TLZMC. TLZMC is one of the few early attempts that deviate from the hybrid-based coding architecture by skipping motion coding. With TLZMC, a low-resolution base layer is utilized to encode temporally unpredictable information. We address the question of whether adapting the base-layer bitrate can achieve better rate-distortion performance. We apply the feature map modulation technique to enable per-frame bitrate adaptation of the base layer. We then propose and compare three online search strategies for determining the base-layer rate parameter: per-level brute-force search, per-level greedy search, and per-frame greedy search. Experimental results show that our top-performing search strategy achieves 0.6%-15.8% Bjontegaard-Delta rate savings over TLZMC.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350359855
ISBN (Print)979-8-3503-5986-2
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 - Jeju, Korea, Republic of
Duration: 4 Dec 20237 Dec 2023

Publication series

NameIEEE International Conference on Visual Communications and Image Processing
ISSN (Print)1018-8770
ISSN (Electronic)2642-9357

Conference

Conference2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
Country/TerritoryKorea, Republic of
CityJeju
Period4 Dec 20237 Dec 2023

Keywords

  • B-frame coding
  • content-Adaptive bit allocation
  • Learned video compression

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Signal Processing
  • Media Technology

Cite this