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

• URL: http://arxiv.org/abs/2512.24300v1
• Date: Tue, 30 Dec 2025 15:41:33 GMT
• Title: Generative Video Compression: Towards 0.01% Compression Rate for Video Transmission
• Authors: Xiangyu Chen, Jixiang Luo, Jingyu Xu, Fangqiu Yi, Chi Zhang, Xuelong Li,
• Abstract summary: We introduce Generative Video Compression (GVC), a new framework that redefines the limits of video compression.<n>GVC encodes video into compact representations and delegates content reconstruction to the receiver.<n>Within the AI Flow framework, GVC opens new possibility for video communication in bandwidth- and resource-constrained environments.
• Score: 43.034936334574155
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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