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Neural Radiance Fields (NeRF) have emerged as a powerful representation for the task of novel view synthesis due to their simplicity and state-of-the-art performance.
Statistics of range images
Jinggang Huang, Ann B. Lee, and David Mumford · 2000
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, and Eero P. Simoncelli · 2004
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Large scale multi-view stereopsis evaluation
Rasmus Ramsbøl Jensen, Anders Lindbjerg Dahl, George Vogiatzis, Engil Tola, and Henrik Aanæs · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Density estimation using real NVP
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2017
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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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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
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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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Controlling neural level sets
Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, and Yaron Lipman · 2019
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Learning shape templates with structured implicit functions
Kyle Genova, Forrester Cole, Daniel Vlasic, Aaron Sarna, William T Freeman, and Thomas Funkhouser · 2019
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Learning to infer implicit surfaces without 3d supervision
Shichen Liu, Shunsuke Saito, Weikai Chen, and Hao Li · 2019
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Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 2019
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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Implicit surface representations as layers in neural networks
Mateusz Michalkiewicz, Jhony K Pontes, Dominic Jack, Mahsa Baktashmotlagh, and Anders Eriksson · 2019
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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
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Occupancy flow: 4d reconstruction by learning particle dynamics
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2019
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Texture fields: Learning texture representations in function space
Michael Oechsle, Lars Mescheder, Michael Niemeyer, Thilo Strauss, and Andreas Geiger · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard A. Newcombe, and Steven Lovegrove · 2019
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Pifu: Pixel-aligned implicit function for high-resolution clothed human digitization
Shunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima, Angjoo Kanazawa, and Hao Li · 2019
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Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
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Portrait neural radiance fields from a single image
Chen Gao, Yichang Shih, Wei-Sheng Lai, Chia-Kai Liang, and Jia-Bin Huang · 2020
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Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
Cited alongside, same era.
Sdfdiff: Differentiable rendering of signed distance fields for 3d shape optimization
Yue Jiang, Dantong Ji, Zhizhong Han, and Matthias Zwicker · 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.
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.
Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
Cited alongside, same era.
DeepSDF: Learning continuous signed distance functions for shape representation
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
Wonbong Jang and Lourdes Agapito · 2021
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Depth-supervised nerf: Fewer views and faster training for free
Jun-Yan Zhu Kangle Deng, Andrew Liu and Deva Ramanan · 2021
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Neural lumigraph rendering
Petr Kellnhofer, Lars C Jebe, Andrew Jones, Ryan Spicer, Kari Pulli, and Gordon Wetzstein · 2021
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Mine: Towards continuous depth mpi with nerf for novel view synthesis
Jiaxin Li, Zijian Feng, Qi She, Henghui Ding, Changhu Wang, and Gim Hee Lee · 2021
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Neural rays for occlusion-aware image-based rendering
Yuan Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Theobalt Christian, Xiaowei Zhou, and Wenping Wang · 2021
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Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2020
Cited alongside, same era.
Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
Cited alongside, same era.
Graf: Generative radiance fields for 3d-aware image synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
Cited alongside, same era.
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein · 2020
Cited alongside, same era.
Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan Barron, and Ren Ng · 2020
Cited alongside, same era.
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
Cited alongside, same era.
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.
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
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Gnerf: Gan-based neural radiance field without posed camera
Quan Meng, Anpei Chen, Haimin Luo, Minye Wu, Hao Su, Lan Xu, Xuming He, and Jingyi Yu · 2021
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Campari: Camera-aware decomposed generative neural radiance fields
Michael Niemeyer and Andreas Geiger · 2021
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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Unisurf: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Sharf: Shape-conditioned radiance fields from a single view
Konstantinos Rematas, Ricardo Martin-Brualla, and Vittorio Ferrari · 2021
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Stochastic neural radiance fields: Quantifying uncertainty in implicit 3d representations
Jianxiong Shen, Adria Ruiz, Antonio Agudo, and Francesc Moreno-Noguer · 2021
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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
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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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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
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Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul P. Srinivasan, Howard Zhou, Jonathan T. Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas A. Funkhouser · 2021
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Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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pixelnerf: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Cips-3d: A 3d-aware generator of gans based on conditionally-independent pixel synthesis
Peng Zhou, Lingxi Xie, Bingbing Ni, and Qi Tian · 2021
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