10 citations · 17 across the 16 of their papers we have counts for
18 papers
SACHA: Semantic-Aware Compression for 3D Gaussian Head Avatars
Zihan Zhang, Shanzhi Yin, Xinju Wu +5
Animatable 3D Gaussian head avatars offer high-fidelity and flexible facial rendering, but typically require substantial storage and transmission costs for numerous Gaussian primit…
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…
AgenticIQA: An Agentic Framework for Adaptive and Interpretable Image Quality Assessment
Hanwei Zhu, Yu Tian, Keyan Ding +4
Image quality assessment (IQA) is inherently complex, as it reflects both the quantification and interpretation of perceptual quality rooted in the human visual system. Conventiona…
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…
Rethinking Generative Human Video Coding with Implicit Motion Transformation
Bolin Chen, Ru-Ling Liao, Jie Chen +1
Beyond traditional hybrid-based video codec, generative video codec could achieve promising compression performance by evolving high-dimensional signals into compact feature repres…
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…
Pleno-Generation: A Scalable Generative Face Video Compression Framework with Bandwidth Intelligence
Bolin Chen, Hanwei Zhu, Shanzhi Yin +5
Generative model based compact video compression is typically operated within a relative narrow range of bitrates, and often with an emphasis on ultra-low rate applications. There…
Generative Human Video Compression with Multi-granularity Temporal Trajectory Factorization
Shanzhi Yin, Bolin Chen, Shiqi Wang +1
In this paper, we propose a novel Multi-granularity Temporal Trajectory Factorization framework for generative human video compression, which holds great potential for bandwidth-co…
Beyond GFVC: A Progressive Face Video Compression Framework with Adaptive Visual Tokens
Bolin Chen, Shanzhi Yin, Zihan Zhang +5
Recently, deep generative models have greatly advanced the progress of face video coding towards promising rate-distortion performance and diverse application functionalities. Beyo…
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…
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…
Generative Visual Compression: A Review
Bolin Chen, Shanzhi Yin, Peilin Chen +2
Artificial Intelligence Generated Content (AIGC) is leading a new technical revolution for the acquisition of digital content and impelling the progress of visual compression towar…
Generative Face Video Coding Techniques and Standardization Efforts: A Review
Bolin Chen, Jie Chen, Shiqi Wang +1
Generative Face Video Coding (GFVC) techniques can exploit the compact representation of facial priors and the strong inference capability of deep generative models, achieving high…
Semantic Face Compression for Metaverse: A Compact 3D Descriptor Based Approach
Binzhe Li, Bolin Chen, Zhao Wang +2
In this letter, we envision a new metaverse communication paradigm for virtual avatar faces, and develop the semantic face compression with compact 3D facial descriptors. The funda…
Interactive Face Video Coding: A Generative Compression Framework
Bolin Chen, Zhao Wang, Binzhe Li +3
In this paper, we propose a novel framework for Interactive Face Video Coding (IFVC), which allows humans to interact with the intrinsic visual representations instead of the signa…