title: Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based
    View Synthesis
summary: While surface-based view synthesis algorithms are appealing due to their low
  computational requirements, they often struggle to reproduce thin structures.
  In contrast, more expensive methods that model the scene's geometry as a
  volumetric density field (e.g. NeRF) excel at reconstructing fine geometric
  detail. However, density fields often represent geometry in a "fuzzy" manner,
  which hinders exact localization of the surface. In this work, we modify
  density fields to encourage them to converge towards surfaces, without
  compromising their ability to reconstruct thin structures. First, we employ a
  discrete opacity grid representation instead of a continuous density field,
  which allows opacity values to discontinuously transition from zero to one at
  the surface. Second, we anti-alias by casting multiple rays per pixel, which
  allows occlusion boundaries and subpixel structures to be modelled without
  using semi-transparent voxels. Third, we minimize the binary entropy of the
  opacity values, which facilitates the extraction of surface geometry by
  encouraging opacity values to binarize towards the end of training. Lastly, we
  develop a fusion-based meshing strategy followed by mesh simplification and
  appearance model fitting. The compact meshes produced by our model can be
  rendered in real-time on mobile devices and achieve significantly higher view
  synthesis quality compared to existing mesh-based approaches.
paper_authors._id: 65d4436c9f087171b8fc4a3d
paper_authors.name: Christian Reiser
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-20T10:47:35.622Z
paper_authors._id: 630b4b11a20a5367811975bd
paper_authors.avatarUrl: /avatars/89b3351a6d542f82e7c8e8a7d352fe82.svg
paper_authors.fullname: Christian Reisert
paper_authors.type: user
paper_authors.user: HeavyRABBIT
paper_authors._id: 65d4436c9f087171b8fc4a3e
paper_authors.name: Stephan Garbin
paper_authors._id: 65d4436c9f087171b8fc4a3f
paper_authors.name: Pratul P. Srinivasan
paper_authors._id: 65d4436c9f087171b8fc4a40
paper_authors.name: Dor Verbin
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-20T10:47:53.337Z
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: 65d4436c9f087171b8fc4a41
paper_authors.name: Richard Szeliski
paper_authors._id: 65d4436c9f087171b8fc4a42
paper_authors.name: Ben Mildenhall
paper_authors._id: 65d4436c9f087171b8fc4a43
paper_authors.name: Jonathan T. Barron
paper_authors._id: 65d4436c9f087171b8fc4a44
paper_authors.name: Peter Hedman
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-20T10:48:28.854Z
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: 65d4436c9f087171b8fc4a45
paper_authors.name: Andreas Geiger
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-20T10:48:35.650Z
paper_authors._id: 620cae049086f3c07f01e3d5
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1644998139538-noauth.jpeg
paper_authors.fullname: Andreas Geiger
paper_authors.type: user
paper_authors.user: andreas-geiger
paper_title: Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based
    View Synthesis
paper_summary: While surface-based view synthesis algorithms are appealing due to their low
  computational requirements, they often struggle to reproduce thin structures.
  In contrast, more expensive methods that model the scene's geometry as a
  volumetric density field (e.g. NeRF) excel at reconstructing fine geometric
  detail. However, density fields often represent geometry in a "fuzzy" manner,
  which hinders exact localization of the surface. In this work, we modify
  density fields to encourage them to converge towards surfaces, without
  compromising their ability to reconstruct thin structures. First, we employ a
  discrete opacity grid representation instead of a continuous density field,
  which allows opacity values to discontinuously transition from zero to one at
  the surface. Second, we anti-alias by casting multiple rays per pixel, which
  allows occlusion boundaries and subpixel structures to be modelled without
  using semi-transparent voxels. Third, we minimize the binary entropy of the
  opacity values, which facilitates the extraction of surface geometry by
  encouraging opacity values to binarize towards the end of training. Lastly, we
  develop a fusion-based meshing strategy followed by mesh simplification and
  appearance model fitting. The compact meshes produced by our model can be
  rendered in real-time on mobile devices and achieve significantly higher view
  synthesis quality compared to existing mesh-based approaches.
paper_ai_summary: The work modifies volumetric density fields to better represent surfaces and thin structures, enabling higher-quality view synthesis with real-time rendering on mobile devices.
paper_ai_keywords: volumetric density field NeRF discrete opacity grid anti-aliasing binary entropy meshing strategy mesh simplification appearance model fitting