Generative Compression for Face Video: A Hybrid Scheme
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Abstract (arXiv)
As the latest video coding standard, versatile video coding (VVC) has shown its ability in retaining pixel quality. To excavate more compression potential for video conference scenarios under ultra-low bitrate, this paper proposes a bitrate adjustable hybrid compression scheme for face video. This hybrid scheme combines the pixel-level precise recovery capability of traditional coding with the generation capability of deep learning based on abridged information, where Pixel wise Bi-Prediction, Low-Bitrate-FOM and Lossless Keypoint Encoder collaborate to achieve PSNR up to 36.23 dB at a low bitrate of 1.47 KB/s. Without introducing any additional bitrate, our method has a clear advantage over VVC under a completely fair comparative experiment, which proves the effectiveness of our proposed scheme. Moreover, our scheme can adapt to any existing encoder / configuration to deal with different encoding requirements, and the bitrate can be dynamically adjusted according to the network condition.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Apr 2022.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 5; 2025: 3.
11 papers.
- 2023Generative Face Video Coding Techniques and Standardization Efforts: A Reviewcited by 19
- 2023Interactive Face Video Coding: A Generative Compression Frameworkcited by 17
- 2024Generative Visual Compression: A Reviewcited by 13
- 2022StableFace: Analyzing and Improving Motion Stability for Talking Face Generationcited by 9
- 2024Generative Human Video Compression with Multi-granularity Temporal Trajectory Factorizationcited by 5
- 2024Standardizing Generative Face Video Compression using Supplemental Enhancement Informationcited by 4
- 2024Tokenizing Motion: A Generative Approach for Scene Dynamics Compressioncited by 3
- 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
- 2024Survey on Visual Signal Coding and Processing with Generative Models: Technologies, Standards and Optimizationcited by 2
- 2025Revising Second Order Terms in Deep Animation Video Codingcited by 0
- 2025Revising Second Order Terms in Deep Animation Video Coding27 Oct 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
- 2024Standardizing Generative Face Video Compression using Supplemental Enhancement Information19 Oct 2024
- 2024Generative Human Video Compression with Multi-granularity Temporal Trajectory Factorization14 Oct 2024
- 2024Tokenizing Motion: A Generative Approach for Scene Dynamics Compression13 Oct 2024
- 2024Survey on Visual Signal Coding and Processing with Generative Models: Technologies, Standards and Optimization23 May 2024
- 2024Generative Visual Compression: A Review3 Feb 2024
- 2023Generative Face Video Coding Techniques and Standardization Efforts: A Review5 Nov 2023
- 2023Interactive Face Video Coding: A Generative Compression Framework20 Feb 2023
- 2022StableFace: Analyzing and Improving Motion Stability for Talking Face Generation29 Aug 2022