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GenStream framework slashes video streaming bandwidth by over 99.9%

By PulseAugur Editorial · [1 sources] ·

Researchers have developed GenStream, a novel framework for streaming human-centric media that significantly reduces bandwidth requirements. Instead of transmitting full video frames, GenStream sends skeletal keypoints, camera viewpoint parameters, and a static 3D background model. A generative model on the client side then reconstructs photorealistic figures and composites them into the scene, achieving over 99.9% bandwidth reduction compared to HEVC. While this shifts computational load to the client, it opens possibilities for advanced avatar synthesis and personalized viewing experiences. AI

IMPACT Enables extreme compression for human-centric media, potentially revolutionizing volumetric video and personalized viewing experiences.

RANK_REASON The cluster contains an arXiv preprint detailing a new technical framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GenStream framework slashes video streaming bandwidth by over 99.9%

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The cluster contains an arXiv preprint detailing a new technical framework. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Emanuele Artioli, Daniele Lorenzi, Shivi Vats, Farzad Tashtarian, Christian Timmerer ·

    GenStream: Semantic Streaming Framework for Generative Reconstruction of Human-centric Media

    arXiv:2609.18634v1 Announce Type: cross Abstract: Video streaming dominates global internet traffic, yet conventional pipelines remain inefficient for structured, human-centric content such as sports, performance, or interactive media. Standard codecs re-encode entire frames, for…

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