Fetching the paper…
Reading the bibliography…
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.
Illumination for computer generated pictures
Bui Tuong Phong · 1975
Earlier work this paper cites.
View interpolation for image synthesis
Shenchang Eric Chen and Lance Williams · 1993
Earlier work this paper cites.
Optical models for direct volume rendering
Nelson Max · 1995
Earlier work this paper cites.
Proposal for a standard default color space for the internet—sRGB
Matthew Anderson, Ricardo Motta, Srinivasan Chandrasekar, and Michael Stokes · 1996
Earlier work this paper cites.
Modeling and rendering architecture from photographs: a hybrid geometry-and image-based approach
Paul E. Debevec, Camillo J. Taylor, and Jitendra Malik · 1996
Earlier work this paper cites.
The lumigraph
Steven J. Gortler, Radek Grzeszczuk, Richard Szeliski, and Michael F. Cohen · 1996
Earlier work this paper cites.
Light field rendering
Marc Levoy and Pat Hanrahan · 1996
Earlier work this paper cites.
A new change of variables for efficient BRDF representation
Szymon M. Rusinkiewicz · 1998
Earlier work this paper cites.
Approximation of glossy reflection with prefiltered environment maps
Jan Kautz and Michael D. McCool · 2000
Earlier work this paper cites.
Surface light fields for 3D photography
Daniel Wood, Daniel Azuma, Wyvern Aldinger, Brian Curless, Tom Duchamp, David Salesin, and Werner Stuetzle · 2000
Earlier work this paper cites.
Unstructured lumigraph rendering
Chris Buehler, Michael Bosse, Leonard McMillan, Steven Gortler, and Michael Cohen · 2001
Earlier work this paper cites.
A signal-processing framework for inverse rendering
Ravi Ramamoorthi and Pat Hanrahan · 2001
Earlier work this paper cites.
Frequency space environment map rendering
Ravi Ramamoorthi and Pat Hanrahan · 2002
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, and Eero P. Simoncelli · 2004
Earlier work this paper cites.
Precomputation-based rendering
Ravi Ramamoorthi · 2009
Earlier work this paper cites.
Image-based rendering for scenes with reflections
Sudipta N. Sinha, Johannes Kopf, Michael Goesele, Daniel Scharstein, and Richard Szeliski · 2012
Earlier work this paper cites.
Image-based rendering in the gradient domain
Johannes Kopf, Fabian Langguth, Daniel Scharstein, Richard Szeliski, and Michael Goesele · 2013
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Cited alongside, same era.
JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 2018
Cited alongside, same era.
Deep blending for free-viewpoint image-based rendering
Peter Hedman, Julien Philip, True Price, Jan-Michael Frahm, George Drettakis, and Gabriel Brostow · 2018
Cited alongside, same era.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
Cited alongside, same era.
Stereo magnification: Learning view synthesis using multiplane images
Multiview neural surface reconstruction by disentangling geometry and appearance
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Ronen Basri, and Yaron Lipman · 2020
Later among the works it cites.
Mip-NeRF: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T. Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P. Srinivasan · 2021
Closest in time.
NeRD: Neural reflectance decomposition from image collections
Mark Boss, Raphael Braun, Varun Jampani, Jonathan T. Barron, Ce Liu, and Hendrik P. A. Lensch · 2021
Closest in time.
Neural-PIL: Neural pre-integrated lighting for reflectance decomposition
Mark Boss, Varun Jampani, Raphael Braun, Ce Liu, Jonathan T. Barron, and Hendrik P. A. Lensch · 2021
Closest in time.
Dynamic neural radiance fields for monocular 4D facial avatar reconstruction
Guy Gafni, Justus Thies, Michael Zollhöfer, and Matthias Nießner · 2021
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely · 2018
Cited alongside, same era.
DeepView: View synthesis with learned gradient descent
John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, and Richard Tucker · 2019
Cited alongside, same era.
Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 2019
Cited alongside, same era.
Local light field fusion: Practical view synthesis with prescriptive sampling guidelines
Ben Mildenhall, Pratul P. Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar · 2019
Cited alongside, same era.
Pushing the boundaries of view extrapolation with multiplane images
Pratul P. Srinivasan, Richard Tucker Joand nathan T. Barron, Ravi Ramamoorthi, Ren Ng, and Noah Snavely · 2019
Cited alongside, same era.
Neural reflectance fields for appearance acquisition
Sai Bi, Zexiang Xu, Pratul P. Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Milos Hasan, Yannick Hold-Geoffroy, David Kriegman, and Ravi Ramamoorthi · 2020
Cited alongside, same era.
Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
Cited alongside, same era.
Baking neural radiance fields for real-time view synthesis
Peter Hedman, Pratul P. Srinivasan, Ben Mildenhall, Jonathan T. Barron, and Paul Debevec · 2021
Closest in time.
NeRF in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan T. Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
Closest in time.
UNISURF: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
Closest in time.
Nerfies: Deformable neural radiance fields
Keunhong Park, Utkarsh Sinha, Jonathan T. Barron, Sofien Bouaziz, Dan B. Goldman, Steven M. Seitz, and Ricardo Martin-Brualla · 2021
Closest in time.
Animatable neural radiance fields for modeling dynamic human bodies
Sida Peng, Junting Dong, Qianqian Wang, Shangzhan Zhang, Qing Shuai, Xiaowei Zhou, and Hujun Bao · 2021
Closest in time.
NeRV: Neural reflectance and visibility fields for relighting and view synthesis
Pratul P. Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik, Ben Mildenhall, and Jonathan T. Barron · 2021
Closest in time.
NeuS: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
Closest in time.
NeX: Real-time view synthesis with neural basis expansion
Suttisak Wizadwongsa, Pakkapon Phongthawee, Jiraphon Yenphraphai, and Supasorn Suwajanakorn · 2021
Closest in time.
Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
Closest in time.
PhySG: Inverse rendering with spherical gaussians for physics-based material editing and relighting
Kai Zhang, Fujun Luan, Qianqian Wang, Kavita Bala, and Noah Snavely · 2021
Closest in time.
NeRFactor: Neural factorization of shape and reflectance under an unknown illumination
Xiuming Zhang, Pratul P. Srinivasan, Boyang Deng, Paul Debevec, William T. Freeman, and Jonathan T. Barron · 2021
Closest in time.