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A classical problem in computer vision is to infer a 3D scene representation from few images that can be used to render novel views at interactive rates.
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.
Street view, 2007
Google · 2007
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Building rome in a day
Sameer Agarwal, Yasutaka Furukawa, Noah Snavely, Ian Simon, Brian Curless, Steven M Seitz, and Richard Szeliski · 2011
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3d mapping in urban environment using geometric featured voxel
Inwook Shim, Yungeun Choe, and Myung Jin Chung · 2011
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A survey of urban reconstruction
Przemyslaw Musialski, Peter Wonka, Daniel G Aliaga, Michael Wimmer, Luc Van Gool, and Werner Purgathofer · 2013
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Octree-based, automatic building facade generation from lidar data
Linh Truong-Hong and Debra F Laefer · 2014
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Occlusion-aware depth estimation using light-field cameras
Ting-Chun Wang, Alexei A Efros, and Ravi Ramamoorthi · 2015
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Depth estimation through a generative model of light field synthesis
Mehdi SM Sajjadi, Rolf Köhler, Bernhard Schölkopf, and Michael Hirsch · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Mesh-based 3d textured urban mapping
Andrea Romanoni, Daniele Fiorenti, and Matteo Matteucci · 2017
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Enhancenet: Single image super-resolution through automated texture synthesis
Mehdi S. M. Sajjadi, Bernhard Scholkopf, and Michael Hirsch · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Neural scene representation and rendering
SM Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, Fabio Viola, Ari S Morcos, Marta Garnelo, Avraham Ruderman, Andrei A Rusu, Ivo Danihelka, Karol Gregor, et al · 2018
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Neural 3d mesh renderer
Hiroharu Kato, Yoshitaka Ushiku, and Tatsuya Harada · 2018
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Learning to navigate in cities without a map
Piotr Mirowski, Matt Grimes, Mateusz Malinowski, Karl Moritz Hermann, Keith Anderson, Denis Teplyashin, Karen Simonyan, Andrew Zisserman, Raia Hadsell, et al · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Stereo Magnification: Learning View Synthesis using Multiplane Images
Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely · 2018
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Soft rasterizer: A differentiable renderer for image-based 3d reasoning
Shichen Liu, Tianye Li, Weikai Chen, and Hao Li · 2019
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Neural rerendering in the wild
Moustafa Meshry, Dan B Goldman, Sameh Khamis, Hugues Hoppe, Rohit Pandey, Noah Snavely, and Ricardo Martin-Brualla · 2019
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Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
NMR Dataset , 2021
Hosted by Niemeyer et al · 2021
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Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
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CodeNeRF: Disentangled Neural Radiance Fields for Object Categories
Wongbong Jang and Lourdes Agapito · 2021
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Transformers in vision: A survey
Salman H. Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, and Mubarak Shah · 2021
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NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, and Danilo Rezende · 2021
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BARF: Bundle-Adjusting Neural Radiance Fields
Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey · 2021
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Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
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Depth estimation from a light field image pair with a generative model
Tao Yan, Fan Zhang, Yiming Mao, Hongbin Yu, Xiaohua Qian, and Rynson WH Lau · 2019
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NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Ben Mildenhall, Pratul Srinivasan, Matthew Tancik, Jonathan Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
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State of the Art on Neural Rendering
Ayush Tewari, Vincent Sitzmann, Stephen Lombardi, Kalyan Sulkavalli, Ricardo Martin-Brualla, Tomas Simon, Matthias Nießner, Gordon Wetzstein, Christian Theobalt, Dan Goldman, and Michael Zollhöfer · 2020
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Official code
PixelNeRF authors · 2021
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Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields
Jonathan Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul Srinivasan · 2021
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NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
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Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
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KiloNeRF: Speeding Up Neural Radiance Fields With Thousands of Tiny MLPs
Christian Reiser, Songyou Peng, Yiyi Liao, and Andreas Geiger · 2021
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Geometry-free view synthesis: Transformers and no 3d priors
Robin Rombach, Patrick Esser, and Björn Ommer · 2021
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Light field networks: Neural scene representations with single-evaluation rendering
Vincent Sitzmann, Semon Rezchikov, William T Freeman, Joshua B Tenenbaum, and Fredo Durand · 2021
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Ayush Tewari, Justus Thies, Ben Mildenhall, Pratul Srinivasan, Edgar Tretschk, Yifan Wang, Christoph Lassner, Vincent Sitzmann, Ricardo Martin-Brualla, Stephen Lombardi, et al · 2021
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GRF: Learning a General Radiance Field for 3D Scene Representation and Rendering
Alex Trevithick and Bo Yang · 2021
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IBRNet: Learning Multi-View Image-Based Rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul Srinivasan, Howard Zhou, Jonathan Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
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Point transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip HS Torr, and Vladlen Koltun · 2021
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Kubric: A Scalable Dataset Generator
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam Laradji, Hsueh-Ti (Derek) Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Oztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, and Andrea Tagliasacchi · 2022
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