Details
| Original language | English |
|---|---|
| Title of host publication | 2025 IEEE International Conference on Multimedia and Expo |
| Subtitle of host publication | Journey to the Center of Machine Imagination, ICME 2025 - Conference Proceedings |
| Publisher | IEEE Computer Society |
| ISBN (electronic) | 9798331594954 |
| ISBN (print) | 979-8-3315-9496-1 |
| Publication status | Published - 30 Jun 2025 |
| Event | 2025 IEEE International Conference on Multimedia and Expo, ICME 2025 - Nantes, France Duration: 30 Jun 2025 → 4 Jul 2025 |
Publication series
| Name | Proceedings - IEEE International Conference on Multimedia and Expo |
|---|---|
| ISSN (Print) | 1945-7871 |
| ISSN (electronic) | 1945-788X |
Abstract
This work proposes a hybrid, explicit-implicit temporal buffering scheme for conditional residual video coding. Recent conditional coding methods propagate implicit temporal information for inter-frame coding, demonstrating superior coding performance to those relying exclusively on previously decoded frames (i.e. the explicit temporal information). However, these methods require substantial memory to store a large number of implicit features. This work presents a hybrid buffering strategy. For inter-frame coding, it buffers one previously decoded frame as the explicit temporal reference and a small number of learned features as implicit temporal reference. Our hybrid buffering scheme for conditional residual coding outperforms the single use of explicit or implicit information. Moreover, it allows the total buffer size to be reduced to the equivalent of two video frames with a negligible performance drop on 2K video sequences. The ablation experiment further sheds light on how these two types of temporal references impact the coding performance.
Keywords
- conditional residual coding, implicit and explicit temporal information buffering, Learned video compression
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Computer Networks and Communications
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2025 IEEE International Conference on Multimedia and Expo: Journey to the Center of Machine Imagination, ICME 2025 - Conference Proceedings. IEEE Computer Society, 2025. (Proceedings - IEEE International Conference on Multimedia and Expo).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Conditional Residual Coding with Explicit-Implicit Temporal Buffering for Learned Video Compression
AU - Chen, Yi Hsin
AU - Ho, Kuan Wei
AU - Benjak, Martin
AU - Ostermann, Jörn
AU - Peng, Wen Hsiao
N1 - Publisher Copyright: © 2025 IEEE.
PY - 2025/6/30
Y1 - 2025/6/30
N2 - This work proposes a hybrid, explicit-implicit temporal buffering scheme for conditional residual video coding. Recent conditional coding methods propagate implicit temporal information for inter-frame coding, demonstrating superior coding performance to those relying exclusively on previously decoded frames (i.e. the explicit temporal information). However, these methods require substantial memory to store a large number of implicit features. This work presents a hybrid buffering strategy. For inter-frame coding, it buffers one previously decoded frame as the explicit temporal reference and a small number of learned features as implicit temporal reference. Our hybrid buffering scheme for conditional residual coding outperforms the single use of explicit or implicit information. Moreover, it allows the total buffer size to be reduced to the equivalent of two video frames with a negligible performance drop on 2K video sequences. The ablation experiment further sheds light on how these two types of temporal references impact the coding performance.
AB - This work proposes a hybrid, explicit-implicit temporal buffering scheme for conditional residual video coding. Recent conditional coding methods propagate implicit temporal information for inter-frame coding, demonstrating superior coding performance to those relying exclusively on previously decoded frames (i.e. the explicit temporal information). However, these methods require substantial memory to store a large number of implicit features. This work presents a hybrid buffering strategy. For inter-frame coding, it buffers one previously decoded frame as the explicit temporal reference and a small number of learned features as implicit temporal reference. Our hybrid buffering scheme for conditional residual coding outperforms the single use of explicit or implicit information. Moreover, it allows the total buffer size to be reduced to the equivalent of two video frames with a negligible performance drop on 2K video sequences. The ablation experiment further sheds light on how these two types of temporal references impact the coding performance.
KW - conditional residual coding
KW - implicit and explicit temporal information buffering
KW - Learned video compression
UR - http://www.scopus.com/inward/record.url?scp=105022664047&partnerID=8YFLogxK
U2 - 10.1109/ICME59968.2025.11209118
DO - 10.1109/ICME59968.2025.11209118
M3 - Conference contribution
AN - SCOPUS:105022664047
SN - 979-8-3315-9496-1
T3 - Proceedings - IEEE International Conference on Multimedia and Expo
BT - 2025 IEEE International Conference on Multimedia and Expo
PB - IEEE Computer Society
T2 - 2025 IEEE International Conference on Multimedia and Expo, ICME 2025
Y2 - 30 June 2025 through 4 July 2025
ER -