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arXiv · 2204.10055

Generative Compression for Face Video: A Hybrid Scheme

Anni Tang·Yan Huang·Jun Ling·Zhiyu Zhang·Yiwei Zhang·Rong Xie·Li Song
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Abstract

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.

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Anni Tang, Yan Huang, Jun Ling, Zhiyu Zhang, Yiwei Zhang, Rong Xie, Li Song. 2022-04-21. Generative Compression for Face Video: A Hybrid Scheme. https://arxiv.org/abs/2204.10055

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