title: NeRF-Casting: Improved View-Dependent Appearance with Consistent
    Reflections
summary: Neural Radiance Fields (NeRFs) typically struggle to reconstruct and render
  highly specular objects, whose appearance varies quickly with changes in
  viewpoint. Recent works have improved NeRF's ability to render detailed
  specular appearance of distant environment illumination, but are unable to
  synthesize consistent reflections of closer content. Moreover, these techniques
  rely on large computationally-expensive neural networks to model outgoing
  radiance, which severely limits optimization and rendering speed. We address
  these issues with an approach based on ray tracing: instead of querying an
  expensive neural network for the outgoing view-dependent radiance at points
  along each camera ray, our model casts reflection rays from these points and
  traces them through the NeRF representation to render feature vectors which are
  decoded into color using a small inexpensive network. We demonstrate that our
  model outperforms prior methods for view synthesis of scenes containing shiny
  objects, and that it is the only existing NeRF method that can synthesize
  photorealistic specular appearance and reflections in real-world scenes, while
  requiring comparable optimization time to current state-of-the-art view
  synthesis models.
paper_authors._id: 6650a0f22fbc9f8285e6ffad
paper_authors.name: Dor Verbin
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-05-24T15:16:14.532Z
paper_authors._id: 6315b0fc915d0b806830b424
paper_authors.avatarUrl: /avatars/e25a7c8df2364c6e8024ec5c646a2889.svg
paper_authors.fullname: Dor Verbin
paper_authors.type: user
paper_authors.user: dorverbin
paper_authors._id: 6650a0f22fbc9f8285e6ffae
paper_authors.name: Pratul P. Srinivasan
paper_authors._id: 6650a0f22fbc9f8285e6ffaf
paper_authors.name: Peter Hedman
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-05-24T15:16:44.507Z
paper_authors._id: 651ec3aee17ef6a94eefc8e7
paper_authors.avatarUrl: /avatars/e90ce400ec0d2de8f9fe4365a6e07b4f.svg
paper_authors.fullname: Peter Hedman
paper_authors.type: user
paper_authors.user: phedman
paper_authors._id: 6650a0f22fbc9f8285e6ffb0
paper_authors.name: Ben Mildenhall
paper_authors._id: 6650a0f22fbc9f8285e6ffb1
paper_authors.name: Benjamin Attal
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-05-24T15:17:01.177Z
paper_authors._id: 63910c04b73a0f8c02a88b74
paper_authors.avatarUrl: /avatars/f099b3f45a683f13537db58a2279bd34.svg
paper_authors.fullname: Benjamin Attal
paper_authors.type: user
paper_authors.user: battal
paper_authors._id: 6650a0f22fbc9f8285e6ffb2
paper_authors.name: Richard Szeliski
paper_authors._id: 6650a0f22fbc9f8285e6ffb3
paper_authors.name: Jonathan T. Barron
paper_title: NeRF-Casting: Improved View-Dependent Appearance with Consistent
    Reflections
paper_summary: Neural Radiance Fields (NeRFs) typically struggle to reconstruct and render
  highly specular objects, whose appearance varies quickly with changes in
  viewpoint. Recent works have improved NeRF's ability to render detailed
  specular appearance of distant environment illumination, but are unable to
  synthesize consistent reflections of closer content. Moreover, these techniques
  rely on large computationally-expensive neural networks to model outgoing
  radiance, which severely limits optimization and rendering speed. We address
  these issues with an approach based on ray tracing: instead of querying an
  expensive neural network for the outgoing view-dependent radiance at points
  along each camera ray, our model casts reflection rays from these points and
  traces them through the NeRF representation to render feature vectors which are
  decoded into color using a small inexpensive network. We demonstrate that our
  model outperforms prior methods for view synthesis of scenes containing shiny
  objects, and that it is the only existing NeRF method that can synthesize
  photorealistic specular appearance and reflections in real-world scenes, while
  requiring comparable optimization time to current state-of-the-art view
  synthesis models.
paper_ai_summary: The proposed method enhances NeRF's rendering of specular objects by using ray tracing and a small network to decode feature vectors, achieving photorealistic reflections with efficient optimization.
paper_ai_keywords: Neural Radiance Fields NeRFs specular objects ray tracing view-dependent radiance feature vectors view synthesis photorealistic specular appearance reflections