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Implicit neural networks have been successfully used for surface reconstruction from point clouds.
Marching cubes: A high resolution 3D surface construction algorithm
William E. Lorensen and Harvey E. Cline · 1987
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Fitting smooth surfaces to dense polygon meshes
Venkat Krishnamurthy and Marc Levoy · 1996
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Simplifying surfaces with color and texture using quadric error metrics
M. Garland and P.S. Heckbert · 1998
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Surface reconstruction using local shape priors
Ran Gal, Ariel Shamir, Tal Hassner, Mark Pauly, and Daniel Cohen-Or · 2007
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Data-dependent MLS for faithful surface approximation
Yaron Lipman, Daniel Cohen-Or, and David Levin · 2007
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Discovering structural regularity in 3D geometry
Mark Pauly, Niloy J. Mitra, Johannes Wallner, Helmut Pottmann, and Leonidas J. Guibas · 2008
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Robust and efficient surface reconstruction from range data
P. Labatut, J. P. Pons, and R. Keriven · 2009
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Completion and reconstruction with primitive shapes
Ruwen Schnabel, Patrick Degener, and Reinhard Klein · 2009
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Robust piecewise-planar 3D reconstruction and completion from large-scale unstructured point data
Anne-Laure Chauve, Patrick Labatut, and Jean-Philippe Pons · 2010
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Signing the unsigned: Robust surface reconstruction from raw pointsets
Patrick Mullen, Fernando De Goes, Mathieu Desbrun, David Cohen-Steiner, and Pierre Alliez · 2010
Earlier work this paper cites.
Multi-view reconstruction preserving weakly-supported surfaces
Michal Jancosek and Tomas Pajdla · 2011
Earlier work this paper cites.
GlobFit: Consistently fitting primitives by discovering global relations
Yangyan Li, Xiaokun Wu, Yiorgos Chrysathou, Andrei Sharf, Daniel Cohen-Or, and Niloy J. Mitra · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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A search-classify approach for cluttered indoor scene understanding
Liangliang Nan, Ke Xie, Andrei Sharf, and Shenzhen Visuca · 2012
Earlier work this paper cites.
High accuracy and visibility-consistent dense multiview stereo
Hoang Hiep Vu, Patrick Labatut, Jean Philippe Pons, and Renaud Keriven · 2012
Earlier work this paper cites.
Surface reconstruction through point set structuring
Lafarge F. and Alliez P · 2013
Earlier work this paper cites.
Screened Poisson surface reconstruction
M.M. Kazhdan and H. Hoppe · 2013
Earlier work this paper cites.
State of the art in surface reconstruction from point clouds
Matthew Berger, Andrea Tagliasacchi, Lee M. Seversky, Pierre Alliez, Joshua A. Levine, Andrei Sharf, and Claudio T. Silva · 2014
Earlier work this paper cites.
Piecewise-planar 3D reconstruction with edge and corner regularization
Alexandre Boulch, Martin de La Gorce, and Renaud Marlet · 2014
Earlier work this paper cites.
Exploiting visibility information in surface reconstruction to preserve weakly supported surfaces
Michal Jancosek and Tomas Pajdla · 2014
Earlier work this paper cites.
ShapeNet: An information-rich 3D model repository, 2015
A.X. Chang, T.A. Funkhouser, L.J. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu · 2015
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SceneNet: Understanding real world indoor scenes with synthetic data, 2015
Ankur Handa, Viorica Patraucean, Vijay Badrinarayanan, Simon Stent, and Roberto Cipolla · 2015
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Adam: A method for stochastic optimization
D.P. Kingma and J. Ba · 2015
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VoxNet: A 3D convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
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3D shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
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Efficient volumetric fusion of airborne and street-side data for urban reconstruction
A. Bódis-Szomorú, H. Riemenschneider, and L. Van Gool · 2016
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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
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3D U-Net: Learning dense volumetric segmentation from sparse annotation
Ö. Çiçek, A. Abdulkadir, S.S. Lienkamp, T. Brox, and O. Ronneberger · 2016
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Understanding real world indoor scenes with synthetic data
Ankur Handa, Viorica Patraucean, Vijay Badrinarayanan, Simon Stent, and Roberto Cipolla · 2016
Earlier work this paper cites.
SceneNet: An annotated model generator for indoor scene understanding
Ankur Handa, Viorica Patraucean, Simon Stent, and Roberto Cipolla · 2016
Earlier work this paper cites.
Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
Earlier work this paper cites.
Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
Earlier work this paper cites.
Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, B. Freeman, and J. Tenenbaum · 2016
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Thingi10k: A dataset of 10,000 3D-printing models
Qingnan Zhou and Alec Jacobson · 2016
Earlier work this paper cites.
Matterport3D: Learning from RGB-D data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niebner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
Earlier work this paper cites.
Shape completion using 3D-encoder-predictor CNNs and shape synthesis
A. Dai, C.R. Qi, and M. Nießner · 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
H. Fan, H. Su, and L.J. Guibas · 2017
Earlier work this paper cites.
Hierarchical surface prediction for 3D object reconstruction
C. Hane, S. Tulsiani, and J. Malik · 2017
Earlier work this paper cites.
Polyfit: Polygonal surface reconstruction from point clouds
Liangliang Nan and Peter Wonka · 2017
Earlier work this paper cites.
PointNet: Deep learning on point sets for 3D classification and segmentation
C.R. Qi, H. Su, K. Mo, and L.J. Guibas · 2017
Earlier work this paper cites.
PointNet++: Deep hierarchical feature learning on point sets in a metric space
C.R. Qi, L. Yi, H. Su, and L.J. Guibas · 2017
Earlier work this paper cites.
OctNetFusion: Learning depth fusion from data
G. Riegler, A.O. Ulusoy, H. Bischof, and A. Geiger · 2017
Earlier work this paper cites.
OctNet: Learning deep 3D representations at high resolutions
G. Riegler, A.O. Ulusoy, and A. Geiger · 2017
Earlier work this paper cites.
Octree generating networks: Efficient convolutional architectures for high-resolution 3D outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
Cited alongside, same era.
Learning representations and generative models for 3D point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
Cited alongside, same era.
ScanComplete: Large-scale scene completion and semantic segmentation for 3D scans
Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Jürgen Sturm, and Matthias Nießner · 2018
Cited alongside, same era.
AtlasNet: A papier-mâché approach to learning 3D surface generation
T. Groueix, M. Fisher, V.G. Kim, B.C. Russell, and M. Aubry · 2018
Cited alongside, same era.
3D-CODED: 3D correspondences by deep deformation
Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, and Mathieu Aubry · 2018
Cited alongside, same era.
Pointwise convolutional neural networks
ConvPoint: Continuous convolutions for point cloud processing
Alexandre Boulch · 2020
Later among the works it cites.
FKAConv: Feature-kernel alignment for point cloud convolution
Alexandre Boulch, Gilles Puy, and Renaud Marlet · 2020
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Learning gradient fields for shape generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan · 2020
Later among the works it cites.
Deep local shapes: Learning local SDF priors for detailed 3D reconstruction
Rohan Chabra, Jan Eric Lenssen, Eddy Ilg, Tanner Schmidt, Julian Straub, S. Lovegrove, and Richard A. Newcombe · 2020
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Implicit functions in feature space for 3D shape reconstruction and completion
J. Chibane, T. Alldieck, and G. Pons-Moll · 2020
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Neural unsigned distance fields for implicit function learning
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Binh-Son Hua, Minh-Khoi Tran, and Sai-Kit Yeung · 2018
Cited alongside, same era.
Robust watertight manifold surface generation method for ShapeNet models
Jingwei Huang, Hao Su, and Leonidas Guibas · 2018
Cited alongside, same era.
Learning category-specific mesh reconstruction from image collections
A. Kanazawa, S. Tulsiani, A.A. Efros, and J. Malik · 2018
Cited alongside, same era.
PointCNN: Convolution on X-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
Cited alongside, same era.
Deep marching cubes: Learning explicit surface representations
Y. Liao, S. Donne, and A. Geiger · 2018
Cited alongside, same era.
Learning efficient point cloud generation for dense 3D object reconstruction
C. Lin, C. Kong, and S. Lucey · 2018
Cited alongside, same era.
3D-LMNet: Latent embedding matching for accurate and diverse 3D point cloud reconstruction from a single image
Priyanka Mandikal, K L Navaneet, Mayank Agarwal, and R Venkatesh Babu · 2018
Cited alongside, same era.
Julian Chibane, Aymen Mir, and Gerard Pons-Moll · 2020
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SG-NN: Sparse generative neural networks for self-supervised scene completion of RGB-D scans
Angela Dai, Christian Diller, and Matthias Nießner · 2020
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CvxNet: Learnable convex decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey Hinton, and Andrea Tagliasacchi · 2020
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Points2Surf: Learning implicit surfaces from point clouds
Philipp Erler, Paul Guerrero, Stefan Ohrhallinger, Niloy J. Mitra, and Michael Wimmer · 2020
Later among the works it cites.
Learning deformable tetrahedral meshes for 3D reconstruction
Jun Gao, Wenzheng Chen, Tommy Xiang, Clement Fuji Tsang, Alec Jacobson, Morgan McGuire, and Sanja Fidler · 2020
Later among the works it cites.
Local deep implicit functions for 3D shape
K. Genova, F. Cole, A. Sud, A. Sarna, and T.A. Funkhouser · 2020
Later among the works it cites.
Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
Later among the works it cites.
NASA: neural articulated shape approximation
T. Jeruzalski, B. Deng, M. Norouzi, J.P. Lewis, G.E. Hinton, and A. Tagliasacchi · 2020
Later among the works it cites.
Local implicit grid representations for 3D scenes
C. Jiang, A. Sud, A. Makadia, J. Huang, M. Nießner, and T. Funkhouser · 2020
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Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
Later among the works it cites.
DIST: rendering deep implicit signed distance function with differentiable sphere tracing
S. Liu, Y. Zhang, S. Peng, B. Shi, M. Pollefeys, and Z. Cui · 2020
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PolyGen: an autoregressive generative model of 3D meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, and Peter W. Battaglia · 2020
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Differentiable volumetric rendering: Learning implicit 3D representations without 3D supervision
M. Niemeyer, L.M. Mescheder, M. Oechsle, and A. Geiger · 2020
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Learning unsupervised hierarchical part decomposition of 3D objects from a single RGB image
D. Paschalidou, L. van Gool, and A. Geiger · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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MetaSDF: Meta-learning signed distance functions
Vincent Sitzmann, Eric R. Chan, Richard Tucker, Noah Snavely, and Gordon Wetzstein · 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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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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PatchNets: Patch-based generalizable deep implicit 3D shape representations
Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Carsten Stoll, and Christian Theobalt · 2020
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Point cloud completion by skip-attention network with hierarchical folding
Xin Wen, Tianyang Li, Z. Han, and Yu-Shen Liu · 2020
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Pix2Vox++: Multi-scale context-aware 3D object reconstruction from single and multiple images
Haozhe Xie, Hongxun Yao, Shengping Zhang, Shangchen Zhou, and Wenxiu Sun · 2020
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SALD: Sign agnostic learning with derivatives
Matan Atzmon and Yaron Lipman · 2021
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Neural-Pull: Learning signed distance functions from point clouds by learning to pull space onto surfaces
Ma Baorui, Han Zhizhong, Liu Yu-shen, and Zwicker Matthias · 2021
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NeeDrop: Self-supervised shape representation from sparse point clouds using needle dropping
Alexandre Boulch, Gilles Puy, and Renaud Marlet · 2021
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Dynamic plane convolutional occupancy networks
Stefan Lionar, Daniil Emtsev, Dusan Svilarkovic, and Songyou Peng · 2021
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DeepDT: Learning geometry from Delaunay triangulation for surface reconstruction
Yiming Luo, Zhenxing Mi, and Wenbing Tao · 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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Shape As Points: A differentiable Poisson solver
Songyou Peng, Chiyu ”Max” Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, and Andreas Geiger · 2021
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Out-of-core surface reconstruction via global TGV minimization
Nikolai Poliarnyi · 2021
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Better aggregation in test-time augmentation
Divya Shanmugam, Davis Blalock, Guha Balakrishnan, and John Guttag · 2021
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RetrievalFuse: Neural 3D scene reconstruction with a database
Yawar Siddiqui, Justus Thies, Fangchang Ma, Qi Shan, Matthias Nießner, and Angela Dai · 2021
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Scalable surface reconstruction with Delaunay-graph neural networks
Raphael Sulzer, Loïc Landrieu, Renaud Marlet, and Bruno Vallet · 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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SA-ConvONet: Sign-agnostic optimization of convolutional occupancy networks
Jiapeng Tang, Jiabao Lei, Dan Xu, Feiying Ma, Kui Jia, and Lei Zhang · 2021
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Adaptive surface reconstruction with multiscale convolutional kernels
Benjamin Ummenhofer and Vladlen Koltun · 2021
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Neural splines: Fitting 3D surfaces with infinitely-wide neural networks
Francis Williams, Matthew Trager, Joan Bruna, and Denis Zorin · 2021
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Continual neural mapping: Learning an implicit scene representation from sequential observations
Zike Yan, Yuxin Tian, Xuesong Shi, Ping Guo, Peng Wang, and Hongbin Zha · 2021
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Sign-agnostic implicit learning of surface self-similarities for shape modeling and reconstruction from raw point clouds
Wenbin Zhao, Jiabao Lei, Yuxin Wen, Jianguo Zhang, and Kui Jia · 2021
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