6 papers
A Cross-Framework Study of Temporal Information Buffering Strategies for Learned Video Compression
Kuan-Wei Ho, Yi-Hsin Chen, Martin Benjak +2
Recent advances in learned video codecs have demonstrated remarkable compression efficiency. Two fundamental design aspects are critical: the choice of inter-frame coding framework…
MH-LVC: Multi-Hypothesis Temporal Prediction for Learned Conditional Residual Video Coding
Huu-Tai Phung, Zong-Lin Gao, Yi-Chen Yao +5
This work, termed MH-LVC, presents a multi-hypothesis temporal prediction scheme that employs long- and short-term reference frames in a conditional residual video coding framework…
HyTIP: Hybrid Temporal Information Propagation for Masked Conditional Residual Video Coding
Yi-Hsin Chen, Yi-Chen Yao, Kuan-Wei Ho +5
Most frame-based learned video codecs can be interpreted as recurrent neural networks (RNNs) propagating reference information along the temporal dimension. This work revisits the…
Conditional Residual Coding with Explicit-Implicit Temporal Buffering for Learned Video Compression
Yi-Hsin Chen, Kuan-Wei Ho, Martin Benjak +2
This work proposes a hybrid, explicit-implicit temporal buffering scheme for conditional residual video coding. Recent conditional coding methods propagate implicit temporal inform…
Fast-OMRA: Fast Online Motion Resolution Adaptation for Neural B-Frame Coding
Sang NguyenQuang, Zong-Lin Gao, Kuan-Wei Ho +2
Most learned B-frame codecs with hierarchical temporal prediction suffer from the domain shift issue caused by the discrepancy in the Group-of-Pictures (GOP) size used for training…
On the Rate-Distortion-Complexity Trade-offs of Neural Video Coding
Yi-Hsin Chen, Kuan-Wei Ho, Martin Benjak +2
This paper aims to delve into the rate-distortion-complexity trade-offs of modern neural video coding. Recent years have witnessed much research effort being focused on exploring t…