PromptMobile: Efficient Promptus for Low Bandwidth Mobile Video Streaming
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Abstract (arXiv)
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).
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 9 of its 21 references that are in the map. First posted on arXiv 20 Mar 2025.
Builds on
9 of 21 references.
References · 9
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,082
- 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,237
- 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,687
- 2023Cache Me if You Can: Accelerating Diffusion Models through Block Cachingcited by 150
- 2023Speed Is All You Need: On-Device Acceleration of Large Diffusion Models via GPU-Aware Optimizationscited by 45
- 2022CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streamingcited by 23
- 2023Reparo: Loss-Resilient Generative Codec for Video Conferencingcited by 8
- 2024Promptus: Can Prompts Streaming Replace Video Streaming with Stable Diffusioncited by 3
- 2024Accelerating Mobile Edge Generation (MEG) by Constrained Learningcited by 3
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- 2026ScalablePromptus: Scalable and High-Fidelity Prompt-Based Video Streaming
- 2026Smaller is Better: Generative Models Can Power Short Video Preloading ↗
- 2025MobileI2V: Fast and High-Resolution Image-to-Video on Mobile Devices
- 2026MobileWan: Closing the Quality Gap for Mobile Video Diffusion
- 2026S2DiT: Sandwich Diffusion Transformer for Mobile Streaming Video Generation
- 2024SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device
- 2022MobileCodec: Neural Inter-frame Video Compression on Mobile Devices
- 2023MobileNVC: Real-time 1080p Neural Video Compression on a Mobile Device