8 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…
Application Space and the Rate-Distortion-Complexity Analysis of Neural Video CODECs
Ricardo L. de Queiroz, Diogo C. Garcia, Yi-Hsin Chen +3
We study the decision-making process for choosing video compression systems through a rate-distortion-complexity (RDC) analysis. We discuss the 2D Bjontegaard delta (BD) metric and…
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…
CAT-3DGS: A Context-Adaptive Triplane Approach to Rate-Distortion-Optimized 3DGS Compression
Yu-Ting Zhan, Cheng-Yuan Ho, Hebi Yang +4
3D Gaussian Splatting (3DGS) has recently emerged as a promising 3D representation. Much research has been focused on reducing its storage requirements and memory footprint. Howeve…