10 papers
Tokenizing Motion: A Generative Approach for Scene Dynamics Compression
Shanzhi Yin, Zihan Zhang, Bolin Chen +2
This paper proposes a novel generative video compression framework that leverages motion pattern priors, derived from subtle dynamics in common scenes (e.g., swaying flowers or a b…
Towards Efficient 3D Gaussian Human Avatar Compression: A Prior-Guided Framework
Shanzhi Yin, Bolin Chen, Xinju Wu +4
This paper proposes an efficient 3D avatar coding framework that leverages compact human priors and canonical-to-target transformation to enable high-quality 3D human avatar video…
Sparse2Dense: A Keypoint-driven Generative Framework for Human Video Compression and Vertex Prediction
Bolin Chen, Ru-Ling Liao, Yan Ye +5
For bandwidth-constrained multimedia applications, simultaneously achieving ultra-low bitrate human video compression and accurate vertex prediction remains a critical challenge, a…
Standardizing Generative Face Video Compression using Supplemental Enhancement Information
Bolin Chen, Yan Ye, Jie Chen +12
This paper proposes a Generative Face Video Compression (GFVC) approach using Supplemental Enhancement Information (SEI), where a series of compact spatial and temporal representat…
A Lightweight Dual-Mode Optimization for Generative Face Video Coding
Zihan Zhang, Shanzhi Yin, Bolin Chen +3
Generative Face Video Coding (GFVC) achieves superior rate-distortion performance by leveraging the strong inference capabilities of deep generative models. However, its practical…
Generative Models at the Frontier of Compression: A Survey on Generative Face Video Coding
Bolin Chen, Shanzhi Yin, Goluck Konuko +4
The rise of deep generative models has greatly advanced video compression, reshaping the paradigm of face video coding through their powerful capability for semantic-aware represen…