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Recently, several works have addressed modeling of 3D shapes using deep neural networks to learn implicit surface representations.
Marching cubes: A high resolution 3d surface construction algorithm
William E Lorensen and Harvey E Cline · 1987
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Point set processing
Pierre Alliez, Laurent Saboret, and Nader Salman · 2010
Earlier work this paper cites.
Rectified linear units improve restricted Boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
Earlier work this paper cites.
Auto-encoding variational Bayes
Diederik P Kingma and Max Welling · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
3D mesh labeling via deep convolutional neural networks
Kan Guo, Dongqing Zou, and Xiaowu Chen · 2015
Earlier work this paper cites.
Voxnet: A 3D convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
Earlier work this paper cites.
Dyna: A model of dynamic human shape in motion
Gerard Pons-Moll, Javier Romero, Naureen Mahmood, and Michael J Black · 2015
Earlier work this paper cites.
3D ShapeNets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
Earlier work this paper cites.
3D-R2N2: A unified approach for single and multi-view 3D object reconstruction
Christopher B Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese · 2016
Earlier work this paper cites.
Differential geometry of curves and surfaces: revised and updated second edition
Manfredo P Do Carmo · 2016
Earlier work this paper cites.
Unsupervised learning of 3D structure from images
Danilo Jimenez Rezende, SM Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, and Nicolas Heess · 2016
Earlier work this paper cites.
A survey of surface reconstruction from point clouds
Matthew Berger, Andrea Tagliasacchi, Lee M Seversky, Pierre Alliez, Gael Guennebaud, Joshua A Levine, Andrei Sharf, and Claudio T Silva · 2017
Earlier work this paper cites.
Dynamic FAUST: Registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2017
Earlier work this paper cites.
Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
Earlier work this paper cites.
Shape completion using 3D-encoder-predictor CNNs and shape synthesis
Angela Dai, Charles Ruizhongtai Qi, and Matthias Nießner · 2017
Earlier work this paper cites.
A point set generation network for 3D object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Hierarchical surface prediction for 3D object reconstruction
Christian Häne, Shubham Tulsiani, and Jitendra Malik · 2017
Earlier work this paper cites.
MobileNets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
Earlier work this paper cites.
SurfaceNet: An end-to-end 3D neural network for multiview stereopsis
Mengqi Ji, Juergen Gall, Haitian Zheng, Yebin Liu, and Lu Fang · 2017
Earlier work this paper cites.
PointNet: Deep learning on point sets for 3D classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Cited alongside, same era.
PointNet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
OctNetFusion: Learning depth fusion from data
Gernot Riegler, Ali Osman Ulusoy, Horst Bischof, and Andreas Geiger · 2017
Cited alongside, same era.
Octree generating networks: Efficient convolutional architectures for high-resolution 3D outputs
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2017
Cited alongside, same era.
Multi-view supervision for single-view reconstruction via differentiable ray consistency
Shubham Tulsiani, Tinghui Zhou, Alexei A Efros, and Jitendra Malik · 2017
Cited alongside, same era.
Photometric mesh optimization for video-aligned 3D object reconstruction
Chen-Hsuan Lin, Oliver Wang, Bryan C Russell, Eli Shechtman, Vladimir G Kim, Matthew Fisher, and Simon Lucey · 2019
Later among the works it cites.
Occupancy networks: Learning 3D reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Later among the works it cites.
Deep level sets: Implicit surface representations for 3D shape inference
Mateusz Michalkiewicz, Jhony K Pontes, Dominic Jack, Mahsa Baktashmotlagh, and Anders Eriksson · 2019
Later among the works it cites.
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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Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, and Alexander Smola · 2017
Cited alongside, same era.
Volumetric performance capture from minimal camera viewpoints
Andrew Gilbert, Marco Volino, John Collomosse, and Adrian Hilton · 2018
Cited alongside, same era.
A papier-mâché approach to learning 3D surface generation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
Cited alongside, same era.
Learning category-specific mesh reconstruction from image collections
Angjoo Kanazawa, Shubham Tulsiani, Alexei A Efros, and Jitendra Malik · 2018
Cited alongside, same era.
Deep marching cubes: Learning explicit surface representations
Yiyi Liao, Simon Donne, and Andreas Geiger · 2018
Cited alongside, same era.
Learning efficient point cloud generation for dense 3D object reconstruction
Chen-Hsuan Lin, Chen Kong, and Simon Lucey · 2018
Cited alongside, same era.
Generating 3D faces using convolutional mesh autoencoders
Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, and Michael J Black · 2018
Cited alongside, same era.
DeepSDF: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Later among the works it cites.
Efficient learning on point clouds with basis point sets
Sergey Prokudin, Christoph Lassner, and Javier Romero · 2019
Later among the works it cites.
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
Later among the works it cites.
Pointflow: 3D point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
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DeepHuman: 3D human reconstruction from a single image
Zerong Zheng, Tao Yu, Yixuan Wei, Qionghai Dai, and Yebin Liu · 2019
Later among the works it cites.
SAL: Sign agnostic learning of shapes from raw data
Matan Atzmon and Yaron Lipman · 2020
Later among the works it cites.
Learning continuous image representation with local implicit image function
Yinbo Chen, Sifei Liu, and Xiaolong Wang · 2020
Later among the works it cites.
Neural unsigned distance fields for implicit function learning
Julian Chibane, Aymen Mir, and Gerard Pons-Moll · 2020
Later among the works it cites.
Implicit feature networks for texture completion from partial 3D data
Julian Chibane and Gerard Pons-Moll · 2020
Later among the works it cites.
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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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 N. P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein · 2020
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Convolutional occupancy networks
Peng Songyou, Michael Niemeyer, Mescheder Lars, and Andreas Geiger Marc, Pollefeys · 2020
Later among the works it cites.
SALD: Sign agnostic learning with derivatives
Matan Atzmon and Yaron Lipman · 2021
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