Tobias Bertel¹    Yusuke Tomoto²    Srinivas Rao²    Rodrigo Ortiz-Cayon²    Stefan Holzer²    Christian Richardt¹

¹ University of Bath       ² Fyusion Inc.

Poster at SIGGRAPH Asia 2020

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Abstract

Image-based rendering methods that support visually pleasing specular surface reflections require accurate surface geometry and a large number of input images. Recent advances in neural scene representations show excellent visual quality while requiring only imperfect mesh proxies or no surface-based proxies at all. While providing state-of-the-art visual quality, the inference time of learned models is usually too slow for interactive applications. While using a casually captured circular video sweep as input, we extend Deferred Neural Rendering to extrapolate smooth viewpoints around specular objects like a car.

Bibtex

@InProceedings{DNR4VE,
  author    = {Tobias Bertel and Yusuke Tomoto and Srinivas Rao and Rodrigo Ortiz-Cayon and Stefan Holzer and Christian Richardt},
  title     = {Deferred Neural Rendering for View Extrapolation},
  booktitle = {SIGGRAPH Asia Posters},
  year      = {2020},
  doi       = {10.1145/3415264.3425441},
  url       = {https://richardt.name/dnr4ve/},
}