Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields

Google (United States) · Harvard University Press

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Abstract

Neural Radiance Fields (NeRF) is a popular view synthesis technique that represents a scene as a continuous volumetric function, parameterized by multilayer perceptrons that provide the volume density and view-dependent emitted radiance at each location. While NeRF-based techniques excel at representing fine geometric structures with smoothly varying view-dependent appearance, they often fail to accurately capture and reproduce the appearance of glossy surfaces. We address this limitation by introducing Ref-NeRF, which replaces NeRF's parameterization of view-dependent outgoing radiance with a representation of reflected radiance and structures this function using a collection of spatially-varying scene…

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481
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Authors

6

Topics & keywords

Keywords
  • Radiance
  • Computer science
  • Representation (politics)
  • Parameterized complexity
  • Artificial intelligence
  • Computer vision
  • Function (biology)
  • Algorithm
UN Sustainable Development Goals
  • Sustainable cities and communities
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