Standardizing Generative Face Video Compression using Supplemental Enhancement Information
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Abstract (arXiv)
This paper proposes a Generative Face Video Compression (GFVC) approach using Supplemental Enhancement Information (SEI), where a series of compact spatial and temporal representations of a face video signal (e.g., 2D/3D keypoints, facial semantics and compact features) can be coded using SEI messages and inserted into the coded video bitstream. At the time of writing, the proposed GFVC approach using SEI messages has been included into a draft amendment of the Versatile Supplemental Enhancement Information (VSEI) standard by the Joint Video Experts Team (JVET) of ISO/IEC JTC 1/SC 29 and ITU-T SG21, which will be standardized as a new version of ITU-T H.274 | ISO/IEC 23002-7. To the best of the authors' knowledge, the JVET work on the proposed SEI-based GFVC approach is the first standardization activity for generative video compression. The proposed SEI approach has not only advanced the reconstruction quality of early-day Model-Based Coding (MBC) via the state-of-the-art generative technique, but also established a new SEI definition for future GFVC applications and deployment. Experimental results illustrate that the proposed SEI-based GFVC approach can achieve remarkable rate-distortion performance compared with the latest Versatile Video Coding (VVC) standard, whilst also potentially enabling a wide variety of functionalities including user-specified animation/filtering and metaverse-related applications.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 16 of its 67 references that are in the map. First posted on arXiv 19 Oct 2024.
Builds on
16 of 67 references.
References · 16
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4 more
- 2023Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective Methodcited by 14
- 2022Generative Compression for Face Video: A Hybrid Schemecited by 11
- 2023Predictive Coding For Animation-Based Video Compressioncited by 9
- 2024Beyond GFVC: A Progressive Face Video Compression Framework with Adaptive Visual Tokenscited by 7
Built on by
Citing papers per year: 2025: 4.
4 papers.
- 2025Pleno-Generation: A Scalable Generative Face Video Compression Framework with Bandwidth Intelligencecited by 3
- 2025Generative Models at the Frontier of Compression: A Survey on Generative Face Video Codingcited by 3
- 2025Sparse2Dense: A Keypoint-driven Generative Framework for Human Video Compression and Vertex Predictioncited by 1
- 2025A Lightweight Dual-Mode Optimization for Generative Face Video Codingcited by 0
- 2025Sparse2Dense: A Keypoint-driven Generative Framework for Human Video Compression and Vertex Prediction27 Sep 2025
- 2025A Lightweight Dual-Mode Optimization for Generative Face Video Coding19 Aug 2025
- 2025Generative Models at the Frontier of Compression: A Survey on Generative Face Video Coding9 Jun 2025
- 2025Pleno-Generation: A Scalable Generative Face Video Compression Framework with Bandwidth Intelligence24 Feb 2025