Fetching the paper…
Reading the bibliography…
The rendering procedure used by neural radiance fields (NeRF) samples a scene with a single ray per pixel and may therefore produce renderings that are excessively blurred or aliased when training or testing images observe scene content at different resolutions.
An improved illumination model for shaded display
Turner Whitted · 1980
Earlier work this paper cites.
Pyramidal parametrics
Lance Williams · 1983
Earlier work this paper cites.
Ray tracing with cones
John Amanatides · 1984
Earlier work this paper cites.
Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
Paul Debevec, C. J. Taylor, and Jitendra Malik · 1992
Earlier work this paper cites.
Optical models for direct volume rendering
Nelson Max · 1995
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.
Tracing ray differentials
Homan Igehy · 1999
Earlier work this paper cites.
Photorealistic scene reconstruction by voxel coloring
Steven M. Seitz and Charles R. Dyer · 1999
Earlier work this paper cites.
Plenoptic sampling
Jin-Xiang Chai, Xin Tong, Shing-Chow Chan, and Heung-Yeung Shum · 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.
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.
Random features for large-scale kernel machines
Ali Rahimi and Benjamin Recht · 2007
Earlier work this paper cites.
Efficient sparse voxel octrees
Samuli Laine and Tero Karras · 2010
Earlier work this paper cites.
LEAN mapping
Marc Olano and Dan Baker · 2010
Earlier work this paper cites.
On the mathematical properties of the structural similarity index
Dominique Brunet, Edward R Vrscay, and Zhou Wang · 2011
Earlier work this paper cites.
Unstructured light fields
Abe Davis, Marc Levoy, and Fredo Durand · 2012
Earlier work this paper cites.
Representing appearance and pre-filtering subpixel data in sparse voxel octrees
Eric Heitz and Fabrice Neyret · 2012
Cited alongside, same era.
Let there be color! Large-scale texturing of 3D reconstructions
Michael Goesele Michael Waechter, Nils Moehrle · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Filtering distributions of normals for shading antialiasing
A. S. Kaplanyan, S. Hill, A. Patney, and A. Lefohn · 2016
Cited alongside, same era.
In-datacenter performance analysis of a tensor processing unit
Norman P Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, et al · 2017
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
JaxNeRF: an efficient JAX implementation of NeRF, 2020
Boyang Deng, Jonathan T. Barron, and Pratul P. Srinivasan · 2020
Later among the works it cites.
Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
Later among the works it cites.
NeRF: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
Later among the works it cites.
Differentiable volumetric rendering: Learning implicit 3D representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
Later among the works it cites.
Deformable neural radiance fields
Keunhong Park, Utkarsh Sinha, Jonathan T. Barron, Sofien Bouaziz, Dan B Goldman, Steven M. Seitz, and Ricardo Martin-Brualla · 2020
Later among the works it cites.
GRAF: Generative radiance fields for 3D-aware image synthesis
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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
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 K. Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar · 2019
Cited alongside, same era.
DeepVoxels: Learning persistent 3D feature embeddings
Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Niessner, Gordon Wetzstein, and Michael Zollhöfer · 2019
Cited alongside, same era.
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
Later among the works it cites.
Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng · 2020
Later among the works it cites.
Multiview neural surface reconstruction by disentangling geometry and appearance
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Basri Ronen, and Yaron Lipman · 2020
Later among the works it cites.
pi-GAN: Periodic implicit generative adversarial networks for 3D-aware image synthesis
Eric R. Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 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.
NeuMIP: Multi-resolution neural materials
Alexandr Kuznetsov, Krishna Mullia, Zexiang Xu, Miloš Hašan, and Ravi Ramamoorthi · 2021
Closest in time.
Neural scene flow fields for space-time view synthesis of dynamic scenes
Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang · 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.
Neural scene graphs for dynamic scenes
Julian Ost, Fahim Mannan, Nils Thuerey, Julian Knodt, and Felix Heide · 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.
Neural geometric level of detail: Real-time rendering with implicit 3d shapes
Towaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai, Alec Jacobson, Morgan McGuire, and Sanja Fidler · 2021
Closest in time.
Learned initializations for optimizing coordinate-based neural representations
Matthew Tancik, Ben Mildenhall, Terrance Wang, Divi Schmidt, Pratul P. Srinivasan, Jonathan T. Barron, and Ren Ng · 2021
Closest in time.