PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming
This work addresses the challenge of low-bandwidth video streaming on mobile devices, offering an incremental improvement over existing Promptus methods.
The paper tackles the problem of Promptus being computationally intensive for real-time mobile video streaming by introducing PromptMobile, an efficient acceleration framework that achieves a 13.6x increase in image generation speed and reduces severely distorted frames by 60% compared to VQGAN.
Traditional video compression algorithms exhibit significant quality degradation at extremely low bitrates. Promptus emerges as a new paradigm for video streaming, substantially cutting down the bandwidth essential for video streaming. However, Promptus is computationally intensive and can not run in real-time on mobile devices. This paper presents PromptMobile, an efficient acceleration framework tailored for on-device Promptus. Specifically, we propose (1) a two-stage efficient generation framework to reduce computational cost by 8.1x, (2) a fine-grained inter-frame caching to reduce redundant computations by 16.6%, (3) system-level optimizations to further enhance efficiency. The evaluations demonstrate that compared with the original Promptus, PromptMobile achieves a 13.6x increase in image generation speed. Compared with other streaming methods, PromptMobile achives an average LPIPS improvement of 0.016 (compared with H.265), reducing 60% of severely distorted frames (compared to VQGAN).