English

NeARportation: A Remote Real-time Neural Rendering Framework

Human-Computer Interaction 2022-10-25 v1 Graphics

Abstract

While the presentation of photo-realistic appearance plays a major role in immersion in an augmented virtuality environment, displaying the photo-realistic appearance of real objects remains a challenging problem. Recent developments in photogrammetry have facilitated the incorporation of real objects into virtual space. However, photo-realistic photogrammetry requires a dedicated measurement environment, and there is a trade-off between measurement cost and quality. Furthermore, even with photo-realistic appearance measurements, there is a trade-off between rendering quality and framerate. There is no framework that could resolve these trade-offs and easily provide a photo-realistic appearance in real-time. Our NeARportation framework combines server-client bidirectional communication and neural rendering to resolve these trade-offs. Neural rendering on the server receives the client's head posture and generates a novel-view image with realistic appearance reproduction, which is streamed onto the client's display. By applying our framework to a stereoscopic display, we confirmed that it could display a high-fidelity appearance on full-HD stereo videos at 35-40 frames-per-second (fps), according to the user's head motion.

Keywords

Cite

@article{arxiv.2210.12398,
  title  = {NeARportation: A Remote Real-time Neural Rendering Framework},
  author = {Yuichi Hiroi and Yuta Itoh and Jun Rekimoto},
  journal= {arXiv preprint arXiv:2210.12398},
  year   = {2022}
}

Comments

5 pages. This is a preprint of a paper accepted at VRST'22 conference. project URL: https://www.ar.c.titech.ac.jp/projects/nearportation-2022

R2 v1 2026-06-28T04:14:40.274Z