title: VR-NeRF: High-Fidelity Virtualized Walkable Spaces
summary: We present an end-to-end system for the high-fidelity capture, model
  reconstruction, and real-time rendering of walkable spaces in virtual reality
  using neural radiance fields. To this end, we designed and built a custom
  multi-camera rig to densely capture walkable spaces in high fidelity and with
  multi-view high dynamic range images in unprecedented quality and density. We
  extend instant neural graphics primitives with a novel perceptual color space
  for learning accurate HDR appearance, and an efficient mip-mapping mechanism
  for level-of-detail rendering with anti-aliasing, while carefully optimizing
  the trade-off between quality and speed. Our multi-GPU renderer enables
  high-fidelity volume rendering of our neural radiance field model at the full
  VR resolution of dual 2Ktimes2K at 36 Hz on our custom demo machine. We
  demonstrate the quality of our results on our challenging high-fidelity
  datasets, and compare our method and datasets to existing baselines. We release
  our dataset on our project website.
paper_authors._id: 6549e5e25d2f6ae0a8ab33d2
paper_authors.name: Linning Xu
paper_authors._id: 6549e5e25d2f6ae0a8ab33d3
paper_authors.name: Vasu Agrawal
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-11-07T14:32:46.963Z
paper_authors._id: 6527fa0f763bcce52dfb1af7
paper_authors.avatarUrl: /avatars/79bdaa7f1948dfec4d9b6139952fbfe1.svg
paper_authors.fullname: Vasu Agrawal
paper_authors.type: user
paper_authors.user: vasuagrawal4
paper_authors._id: 6549e5e25d2f6ae0a8ab33d4
paper_authors.name: William Laney
paper_authors._id: 6549e5e25d2f6ae0a8ab33d5
paper_authors.name: Tony Garcia
paper_authors._id: 6549e5e25d2f6ae0a8ab33d6
paper_authors.name: Aayush Bansal
paper_authors._id: 6549e5e25d2f6ae0a8ab33d7
paper_authors.name: Changil Kim
paper_authors._id: 6549e5e25d2f6ae0a8ab33d8
paper_authors.name: Samuel Rota Bulò
paper_authors._id: 6549e5e25d2f6ae0a8ab33d9
paper_authors.name: Lorenzo Porzi
paper_authors._id: 6549e5e25d2f6ae0a8ab33da
paper_authors.name: Peter Kontschieder
paper_authors._id: 6549e5e25d2f6ae0a8ab33db
paper_authors.name: Aljaž Božič
paper_authors._id: 6549e5e25d2f6ae0a8ab33dc
paper_authors.name: Dahua Lin
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-11-07T14:42:52.858Z
paper_authors._id: 636317ed80c1a705a6eff396
paper_authors.avatarUrl: /avatars/3db090e101b916d9256d0d3e043db71d.svg
paper_authors.fullname: Dahua Lin
paper_authors.type: user
paper_authors.user: lindahua
paper_authors._id: 6549e5e25d2f6ae0a8ab33dd
paper_authors.name: Michael Zollhöfer
paper_authors._id: 6549e5e25d2f6ae0a8ab33de
paper_authors.name: Christian Richardt
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-13T20:37:01.089Z
paper_authors._id: 67adc0cfe1f8b9375a6c7a63
paper_authors.avatarUrl: /avatars/942d92ff9bd9e7a0f8f4687babbb8153.svg
paper_authors.fullname: Christian Richardt
paper_authors.type: user
paper_authors.user: cr333
paper_title: VR-NeRF: High-Fidelity Virtualized Walkable Spaces
paper_summary: We present an end-to-end system for the high-fidelity capture, model
  reconstruction, and real-time rendering of walkable spaces in virtual reality
  using neural radiance fields. To this end, we designed and built a custom
  multi-camera rig to densely capture walkable spaces in high fidelity and with
  multi-view high dynamic range images in unprecedented quality and density. We
  extend instant neural graphics primitives with a novel perceptual color space
  for learning accurate HDR appearance, and an efficient mip-mapping mechanism
  for level-of-detail rendering with anti-aliasing, while carefully optimizing
  the trade-off between quality and speed. Our multi-GPU renderer enables
  high-fidelity volume rendering of our neural radiance field model at the full
  VR resolution of dual 2Ktimes2K at 36 Hz on our custom demo machine. We
  demonstrate the quality of our results on our challenging high-fidelity
  datasets, and compare our method and datasets to existing baselines. We release
  our dataset on our project website.
paper_ai_summary: The system captures, reconstructs, and renders high-fidelity walkable spaces using neural radiance fields, achieving high-quality real-time VR rendering with a custom dataset and multi-camera rig.
paper_ai_keywords: neural radiance fields multi-camera rig HDR appearance perceptual color space mip-mapping level-of-detail rendering anti-aliasing multi-GPU renderer VR resolution volume rendering high-fidelity datasets