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Coordinate networks like Multiplicative Filter Networks (MFNs) and BACON offer some control over the frequency spectrum used to represent continuous signals such as images or 3D volumes.
Pyramid methods in image processing
Edward H Adelson, Charles H Anderson, James R Bergen, Peter J Burt, and Joan M Ogden · 1984
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The laplacian pyramid as a compact image code
Peter J Burt and Edward H Adelson · 1987
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Wavelets and signal processing
Olivier Rioul and Martin Vetterli · 1991
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Wavelets and filter banks: Theory and design
Martin Vetterli and Cormac Herley · 1992
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The steerable pyramid: A flexible architecture for multi-scale derivative computation
Eero P. Simoncelli and William T. Freeman · 1995
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A wavelet tour of signal processing
Stéphane Mallat · 1999
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Three-dimensional spectral signal-to-noise ratio for a class of reconstruction algorithms
Pawel A Penczek · 2002
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Accurate determination of local defocus and specimen tilt in electron microscopy
Joseph A Mindell and Nikolaus Grigorieff · 2003
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Fourier shell correlation threshold criteria
Marin Van Heel and Michael Schatz · 2005
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EMAN2: an extensible image processing suite for electron microscopy
Guang Tang, Liwei Peng, Philip R Baldwin, Deepinder S Mann, Wen Jiang, Ian Rees, and Steven J Ludtke · 2007
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Relion: implementation of a bayesian approach to cryo-EM structure determination
Sjors HW Scheres · 2012
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The resolution revolution
Werner Kühlbrandt · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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cryosparc: algorithms for rapid unsupervised cryo-EM structure determination
Ali Punjani, John L Rubinstein, David J Fleet, and Marcus A Brubaker · 2017
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Rapid solution of the cryo-em reconstruction problem by frequency marching
Alex Barnett, Leslie Greengard, Andras Pataki, and Marina Spivak · 2017
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Ucsf chimerax: Meeting modern challenges in visualization and analysis
Thomas D Goddard, Conrad C Huang, Elaine C Meng, Eric F Pettersen, Gregory S Couch, John H Morris, and Thomas E Ferrin · 2018
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Multigrid methods
James H Bramble · 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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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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DeepSDF: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard 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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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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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
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Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien NP Martel, Alexander W Bergman, David B Lindell, and Gordon Wetzstein · 2020
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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
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inerf: Inverting neural radiance fields for pose estimation
Lin Yen-Chen, Pete Florence, Jonathan T Barron, Alberto Rodriguez, Phillip Isola, and Tsung-Yi Lin · 2021
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D-NeRF: Neural radiance fields for dynamic scenes
Albert Pumarola, Enric Corona, Gerard Pons-Moll, and Francesc Moreno-Noguer · 2021
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AutoInt: Automatic integration for fast neural volume rendering
David B. Lindell, Julien N. P. Martel, and Gordon Wetzstein · 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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UNISURF: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
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Neural lumigraph rendering
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Deep local shapes: Learning local SDF priors for detailed 3D reconstruction
Rohan Chabra, Jan Eric Lenssen, Eddy Ilg, Tanner Schmidt, Julian Straub, Steven Lovegrove, and Richard Newcombe · 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.
Local deep implicit functions for 3D shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas Funkhouser · 2020
Cited alongside, same era.
Local implicit grid representations for 3D scenes
Chiyu Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, and Thomas Funkhouser · 2020
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Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
Cited alongside, same era.
Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
Cited alongside, same era.
Theory of calculation of images of thick specimens
Earl J Kirkland · 2020
Cited alongside, same era.
Petr Kellnhofer, Lars Jebe, Andrew Jones, Ryan Spicer, Kari Pulli, and Gordon Wetzstein · 2021
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Dynamic CT reconstruction from limited views with implicit neural representations and parametric motion fields
Albert W Reed, Hyojin Kim, Rushil Anirudh, K Aditya Mohan, Kyle Champley, Jingu Kang, and Suren Jayasuriya · 2021
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Coil: Coordinate-based internal learning for imaging inverse problems
Yu Sun, Jiaming Liu, Mingyang Xie, Brendt Wohlberg, and Ulugbek S Kamilov · 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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ACORN: Adaptive coordinate networks for neural scene representation
Julien N. P. Martel, David B. Lindell, Connor Z. Lin, Eric R. Chan, Marco Monteiro, and Gordon Wetzstein · 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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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
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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
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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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3D flexible refinement: structure and motion of flexible proteins from cryo-EM
Ali Punjani and David J Fleet · 2021
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CryoAI: Amortized inference of poses for ab initio reconstruction of 3D molecular volumes from real cryo-EM images
Axel Levy, Frédéric Poitevin, Julien Martel, Youssef Nashed, Ariana Peck, Nina Miolane, Daniel Ratner, Mike Dunne, and Gordon Wetzstein · 2022
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Bacon: Band-limited coordinate networks for multiscale scene representation
David B Lindell, Dave Van Veen, Jeong Joon Park, and Gordon Wetzstein · 2022
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Geometry-consistent neural shape representation with implicit displacement fields
Wang Yifan, Lukas Rahmann, and Olga Sorkine-Hornung · 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 Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, and Gordon Wetzstein · 2022
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Gram: Generative radiance manifolds for 3D-aware image generation
Yu Deng, Jiaolong Yang, Jianfeng Xiang, and Xin Tong · 2022
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Stylesdf: High-resolution 3D-consistent image and geometry generation
Roy Or-El, Xuan Luo, Mengyi Shan, Eli Shechtman, Jeong Joon Park, and Ira Kemelmacher-Shlizerman · 2022
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