Dense-Prior-Guided Generative Video Compression
Diffusion-based generative video compression offers a promising paradigm for low-bitrate reconstruction, but existing keyframe-based controllable approaches rely on sparse priors for non-keyframes, which often lack sufficient low-level details for faithful reconstruction and require non-trivial training to adapt generative models to specialized controls. We propose Dense-Prior-Guided Generative Video Compression (DGVC), a training-free framework that uses codec-compressed luminance components of non-keyframes as dense priors to guide reconstruction. Unlike sparse controls, the dense luminance priors are compatible with modern fidelity-oriented video codecs and remain sufficiently faithful...
| Authors | Ding Ding, Daowen Li, Yixin Gao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 April 2026 |
| Last updated at source | 19 September 2026 |
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