Generative Video Compression: Towards 0.01% Compression Rate for Video Transmission

TL;DR

This paper introduces Generative Video Compression (GVC), a novel framework that achieves extremely high compression rates near 0.02% by leveraging generative models, enabling efficient video transmission in bandwidth-constrained environments.

Contribution

The paper presents GVC, a new generative-based video compression framework that significantly reduces transmission bandwidth by shifting reconstruction to the receiver, with practical deployment strategies.

Findings

Achieved 0.02% compression rate in some cases.

Demonstrated GVC's effectiveness in resource-constrained environments.

Proposed a compression-computation trade-off for practical deployment.

Abstract

Whether a video can be compressed at an extreme compression rate as low as 0.01%? To this end, we achieve the compression rate as 0.02% at some cases by introducing Generative Video Compression (GVC), a new framework that redefines the limits of video compression by leveraging modern generative video models to achieve extreme compression rates while preserving a perception-centric, task-oriented communication paradigm, corresponding to Level C of the Shannon-Weaver model. Besides, How we trade computation for compression rate or bandwidth? GVC answers this question by shifting the burden from transmission to inference: it encodes video into extremely compact representations and delegates content reconstruction to the receiver, where powerful generative priors synthesize high-quality video from minimal transmitted information. Is GVC practical and deployable? To ensure practical deployment, we propose a compression-computation trade-off strategy, enabling fast inference on consume-grade GPUs. Within the AI Flow framework, GVC opens new possibility for video communication in bandwidth- and resource-constrained environments such as emergency rescue, remote surveillance, and mobile edge computing. Through empirical validation, we demonstrate that GVC offers a viable path toward a new effective, efficient, scalable, and practical video communication paradigm.