7 papers
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…
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…
Compressing Human Body Video with Interactive Semantics: A Generative Approach
Bolin Chen, Shanzhi Yin, Hanwei Zhu +6
In this paper, we propose to compress human body video with interactive semantics, which can facilitate video coding to be interactive and controllable by manipulating semantic-lev…
Leveraging Diffusion Knowledge for Generative Image Compression with Fractal Frequency-Aware Band Learning
Lingyu Zhu, Xiangrui Zeng, Bolin Chen +3
By optimizing the rate-distortion-realism trade-off, generative image compression approaches produce detailed, realistic images instead of the only sharp-looking reconstructions pr…