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Neural Radiance Fields (NeRF) is a technique for high quality novel view synthesis from a collection of posed input images.
Distributed ray tracing
Robert L. Cook, Thomas Porter, and Loren Carpenter · 1984
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A realistic camera model for computer graphics
Craig Kolb, Don Mitchell, and Pat Hanrahan · 1995
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The lumigraph
Steven J Gortler, Radek Grzeszczuk, Richard Szeliski, and Michael F Cohen · 1996
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Light field rendering
Marc Levoy and Pat Hanrahan · 1996
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Recovering high dynamic range radiance maps from photographs
Paul E. Debevec and Jitendra Malik · 1997
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Unstructured lumigraph rendering
Chris Buehler, Michael Bosse, Leonard McMillan, Steven Gortler, and Michael Cohen · 2001
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Image denoising by sparse 3-d transform-domain collaborative filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
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Practical poissonian-gaussian noise modeling and fitting for single-image raw-data
Alessandro Foi, Mejdi Trimeche, Vladimir Katkovnik, and Karen O. Egiazarian · 2008
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Image demosaicing: A systematic survey
Xin Li, Bahadir Gunturk, and Lei Zhang · 2008
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Learning photographic global tonal adjustment with a database of input / output image pairs
Vladimir Bychkovsky, Sylvain Paris, Eric Chan, and Frédo Durand · 2011
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Fast bilateral-space stereo for synthetic defocus
Jonathan T. Barron, Andrew Adams, YiChang Shih, and Carlos Hernández · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Deepstereo: Learning to predict new views from the world’s imagery
John Flynn, Ivan Neulander, James Philbin, and Noah Snavely · 2016
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Burst photography for high dynamic range and low-light imaging on mobile cameras
Samuel W. Hasinoff, Dillon Sharlet, Ryan Geiss, Andrew Adams, Jonathan T.. Barron, Florian Kainz, Jiawen Chen, and Marc Levoy · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Hdr image reconstruction from a single exposure using deep cnns
Gabriel Eilertsen, Joel Kronander, Gyorgy Denes, Rafał Mantiuk, and Jonas Unger · 2017
Earlier work this paper cites.
Deep bilateral learning for real-time image enhancement
Michaël Gharbi, Jiawen Chen, Jonathan T Barron, Samuel W Hasinoff, and Frédo Durand · 2017
Earlier work this paper cites.
Deep high dynamic range imaging of dynamic scenes
Nima Khademi Kalantari and Ravi Ramamoorthi · 2017
Earlier work this paper cites.
Benchmarking denoising algorithms with real photographs
Tobias Plötz and Stefan Roth · 2017
Cited alongside, same era.
Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
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Learning to see in the dark
Chen Chen, Qifeng Chen, Jia Xu, and Vladlen Koltun · 2018
Cited alongside, same era.
Deep burst denoising
Clement Godard, Kevin Matzen, and Matt Uyttendaele · 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.
Exposure: A white-box photo post-processing framework
Yuanming Hu, Hao He, Chenxi Xu, Baoyuan Wang, and Stephen Lin · 2018
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
Later among the works it cites.
Synthetic defocus and look-ahead autofocus for casual videography
Xuaner Zhang, Kevin Matzen, Vivien Nguyen, Dillon Yao, You Zhang, and Ren Ng · 2019
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.
Free view synthesis
Gernot Riegler and Vladlen Koltun · 2020
Later among the works it cites.
Supervised raw video denoising with a benchmark dataset on dynamic scenes
Huanjing Yue, Cong Cao, Lei Liao, Ronghe Chu, and Jingyu Yang · 2020
Later among the works it cites.
Törf: Time-of-flight radiance fields for dynamic scene view synthesis, 2021
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Noise2noise: Learning image restoration without clean data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, and Timo Aila · 2018
Cited alongside, same era.
Burst denoising with kernel prediction networks
Ben Mildenhall, Jonathan T. Barron, Jiawen Chen, Dillon Sharlet, Ren Ng, and Robert Carroll · 2018
Cited alongside, same era.
Aperture supervision for monocular depth estimation
Pratul P. Srinivasan, Rahul Garg, Neal Wadhwa, Ren Ng, and Jonathan T. Barron · 2018
Cited alongside, same era.
Synthetic depth-of-field with a single-camera mobile phone
Neal Wadhwa, Rahul Garg, David E. Jacobs, Bryan E. Feldman, Nori Kanazawa, Robert Carroll, Yair Movshovitz-Attias, Jonathan T. Barron, Yael Pritch, and Marc Levoy · 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.
Noise2self: Blind denoising by self-supervision
Joshua Batson and Loic Royer · 2019
Cited alongside, same era.
Benjamin Attal, Eliot Laidlaw, Aaron Gokaslan, Changil Kim, Christian Richardt, James Tompkin, and Matthew O’Toole · 2021
Closest in time.
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.
Depth-supervised nerf: Fewer views and faster training for free
Jun-Yan Zhu Kangle Deng, Andrew Liu and Deva Ramanan · 2021
Closest in time.
Point-based neural rendering with per-view optimization
Georgios Kopanas, Julien Philip, Thomas Leimkühler, and George Drettakis · 2021
Closest in time.
BARF: Bundle-adjusting neural radiance fields
Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey · 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.
Stable view synthesis
Gernot Riegler and Vladlen Koltun · 2021
Closest in time.
Adop: Approximate differentiable one-pixel point rendering, 2021
Darius Rückert, Linus Franke, and Marc Stamminger · 2021
Closest in time.
Unsupervised deep video denoising
Dev Yashpal Sheth, Sreyas Mohan, Joshua Vincent, Ramon Manzorro, Peter A. Crozier, Mitesh M. Khapra, Eero P. Simoncelli, and Carlos Fernandez-Granda · 2021
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Nerfingmvs: Guided optimization of neural radiance fields for indoor multi-view stereo
Yi Wei, Shaohui Liu, Yongming Rao, Wang Zhao, Jiwen Lu, and Jie Zhou · 2021
Closest in time.
Self-calibrating neural radiance fields
Christopehr Choy Animashree Anandkumar Minsu Cho Yoonwoo Jeong, Seokjun Ahn and Jaesik Park · 2021
Closest in time.
In-place scene labelling and understanding with implicit scene representation
Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger, and Andrew Davison · 2021
Closest in time.