Promptus: Can Prompt Streaming Replace Video Streaming

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Authors: Association for Artificial Intelligence 2026, Junlin Hao, Liming Liu, Yunpeng Tan, Jiangkai Wu, Liang Zhang, Xinggong ZHANG
Cited by: 0

Abstract

With the exponential growth of video traffic, traditional video streaming systems are approaching their limits in communication capacity. To further reduce bitrate while maintaining quality, we propose Promptus, a disruptive semantic communication system that streaming prompts instead of videos, which represents real-world video frames with a series of "prompts" for delivery and employs Stable Diffusion to generate the same video at the receiver. To ensure that the generated video is pixel-aligned with the original video, a gradient descent-based prompt fitting framework is proposed. Further, a low-rank decomposition-based bitrate control algorithm is introduced to achieve adaptive bitrate. For inter-frame compression, an interpolation-aware fitting algorithm is proposed. Evaluations across various video genres demonstrate that, compared to H.265, Promptus can achieve more than a 4x bandwidth reduction while preserving the same perceptual quality. On the other hand, at extremely low bitrates, Promptus can enhance the perceptual quality by 0.139 and 0.118 (in LPIPS) compared to VAE and H.265, respectively, and decreases the ratio of severely distorted frames by 89.3% and 91.7%. Our work opens up a new paradigm for efficient video communication. Promptus is open-sourced at the supplementary material. Please refer to the code appendix.

Fields of Study & Subjects

Video Coding and Compression Technologies Image and Video Quality Assessment Generative Adversarial Networks and Image Synthesis

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN