Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
Google (United States) · Harvard University Press
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…
Citation impact
- FWCI
- 27.16
- Percentile
- 100%
- References
- 56
Authors
6Topics & keywords
- Radiance
- Computer science
- Representation (politics)
- Parameterized complexity
- Artificial intelligence
- Computer vision
- Function (biology)
- Algorithm
- Sustainable cities and communities