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Recent efforts in Neural Rendering Fields (NeRF) have shown impressive results on novel view synthesis by utilizing implicit neural representation to represent 3D scenes.
Ray tracing volume densities
James T Kajiya and Brian P Von Herzen · 1984
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Optical models for direct volume rendering
Nelson Max · 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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Image quality assessment: from error visibility to structural similarity
Zhou Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli · 2004
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Model compression
Cristian Buciluǎ, Rich Caruana, and Alexandru Niculescu-Mizil · 2006
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2014
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Adam: A method for stochastic optimization, 2014
Diederik P. Kingma and Jimmy Ba · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift, 2015
Sergey Ioffe and Christian Szegedy · 2015
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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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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Deep learning using rectified linear units (relu)
Abien Fred Agarap · 2018
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Efficient sparse-winograd convolutional neural networks
Xingyu Liu, Jeff Pool, Song Han, and William J Dally · 2018
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The unreasonable effectiveness of deep features as a perceptual metric, 2018
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
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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.
Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Nerf-pytorch
Lin Yen-Chen · 2020
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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
Cited alongside, same era.
Use coremltools to convert models from third-party libraries to core ml., 2021
Nex: Real-time view synthesis with neural basis expansion
Suttisak Wizadwongsa, Pakkapon Phongthawee, Jiraphon Yenphraphai, and Supasorn Suwajanakorn · 2021
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Plenoctrees for real-time rendering of neural radiance fields
Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, and Angjoo Kanazawa · 2021
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Learning neural light fields with ray-space embedding
Benjamin Attal, Jia-Bin Huang, Michael Zollhöfer, Johannes Kopf, and Changil Kim · 2022
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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T Barron, Ben Mildenhall, Dor Verbin, Pratul P Srinivasan, and Peter Hedman · 2022
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Efficient geometry-aware 3d generative adversarial networks
Eric R Chan, Connor Z Lin, Matthew A Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas J Guibas, Jonathan Tremblay, Sameh Khamis, et al · 2022
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CoreMLTools · 2021
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Fastnerf: High-fidelity neural rendering at 200fps
Stephan J Garbin, Marek Kowalski, Matthew Johnson, Jamie Shotton, and Julien Valentin · 2021
Cited alongside, same era.
Stylenerf: A style-based 3d-aware generator for high-resolution image synthesis
Jiatao Gu, Lingjie Liu, Peng Wang, and Christian Theobalt · 2021
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
Cited alongside, same era.
Autoint: Automatic integration for fast neural volume rendering
David B Lindell, Julien NP Martel, and Gordon Wetzstein · 2021
Cited alongside, same era.
DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks
Thomas Neff, Pascal Stadlbauer, Mathias Parger, Andreas Kurz, Joerg H. Mueller, Chakravarty R. Alla Chaitanya, Anton S. Kaplanyan, and Markus Steinberger · 2021
Cited alongside, same era.
Derf: Decomposed radiance fields
Daniel Rebain, Wei Jiang, Soroosh Yazdani, Ke Li, Kwang Moo Yi, and Andrea Tagliasacchi · 2021
Cited alongside, same era.
Zhiqin Chen, Thomas Funkhouser, Peter Hedman, and Andrea Tagliasacchi · 2022
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Plenoxels: Radiance fields without neural networks
Fridovich-Keil and Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa · 2022
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Headnerf: A realtime nerf-based parametric head model
Yang Hong, Bo Peng, Haiyao Xiao, Ligang Liu, and Juyong Zhang · 2022
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Rethinking vision transformers for mobilenet size and speed
Yanyu Li, Ju Hu, Yang Wen, Georgios Evangelidis, Kamyar Salahi, Yanzhi Wang, Sergey Tulyakov, and Jian Ren · 2022
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Efficientformer: Vision transformers at mobilenet speed
Yanyu Li, Geng Yuan, Yang Wen, Eric Hu, Georgios Evangelidis, Sergey Tulyakov, Yanzhi Wang, and Jian Ren · 2022
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Neulf: Efficient novel view synthesis with neural 4d light field
Celong Liu, Zhong Li, Junsong Yuan, and Yi Xu · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Ref-nerf: Structured view-dependent appearance for neural radiance fields
Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T Barron, and Pratul P Srinivasan · 2022
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R2l: Distilling neural radiance field to neural light field for efficient novel view synthesis
Huan Wang, Jian Ren, Zeng Huang, Kyle Olszewski, Menglei Chai, Yun Fu, and Sergey Tulyakov · 2022
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