Details
Original language | English |
---|---|
Title of host publication | 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (electronic) | 9798350359855 |
ISBN (print) | 979-8-3503-5986-2 |
Publication status | Published - 2023 |
Event | 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 - Jeju, Korea, Republic of Duration: 4 Dec 2023 → 7 Dec 2023 |
Publication series
Name | IEEE International Conference on Visual Communications and Image Processing |
---|---|
ISSN (Print) | 1018-8770 |
ISSN (electronic) | 2642-9357 |
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.
Keywords
- B-frame coding, content-Adaptive bit allocation, Learned video compression
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Hardware and Architecture
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Media Technology
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (IEEE International Conference on Visual Communications and Image Processing).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Rate Adaptation for Learned Two-layer B-frame Coding without Signaling Motion Information
AU - Xie, Hong Sheng
AU - Chen, Yi Hsin
AU - Peng, Wen Hsiao
AU - Benjak, Martin
AU - Ostermann, Jorn
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - B-frame coding
KW - content-Adaptive bit allocation
KW - Learned video compression
UR - http://www.scopus.com/inward/record.url?scp=85184857498&partnerID=8YFLogxK
U2 - 10.1109/VCIP59821.2023.10402774
DO - 10.1109/VCIP59821.2023.10402774
M3 - Conference contribution
AN - SCOPUS:85184857498
SN - 979-8-3503-5986-2
T3 - IEEE International Conference on Visual Communications and Image Processing
BT - 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
Y2 - 4 December 2023 through 7 December 2023
ER -