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XRStream

Generates photorealistic 3D avatars from ordinary 2D images, enabling holographic telepresence without specialist capture hardware.

Lead researcher
Steven Davy
Institution
Technological University Dublin
XRStream

About the project

Holographic communication holds transformative potential for remote work, education, and telemedicine—but current systems require high bandwidth and expensive, specialised hardware. XRStream provides a solution: using AI to enable photorealistic holographic telepresence from simple 2D image inputs, dramatically lowering cost and infrastructure requirements. The system applies deep generative models and GPU acceleration at the edge to reconstruct and render realistic 3D avatars in real time, enabling immersive XR communication without 3D capture hardware.

The key objectives of XRStream are:

1.Real-time inference and model compression for ultra-fast performance.
2.GPU-accelerated rendering on affordable devices.
3.Low-latency communication over common high-bandwidth networks (e.g. 5G).

Target milestones include optimised inference models, GPU rendering deployment, end-to-end system integration, and full-scale user validation.The ultimate goal is to enable affordable holographic conferencing for broad market adoption.

Last updated: 8 September 2026

Project team

Steven Davy

Lead researcher
Technological University Dublin

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