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Implicit neural representation is a recent approach to learn shape collections as zero level-sets of neural networks, where each shape is represented by a latent code.
Shape distributions
Robert Osada, Thomas Funkhouser, Bernard Chazelle, and David Dobkin · 2002
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As-rigid-as-possible surface modeling
Olga Sorkine and Marc Alexa · 2007
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H-infinity optimal control and related minimax design problems: a dynamic game approach
Tamer Başar and Pierre Bernhard · 2008
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A concise and provably informative multi-scale signature based on heat diffusion
Jian Sun, Maks Ovsjanikov, and Leonidas Guibas · 2009
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On discrete killing vector fields and patterns on surfaces
Mirela Ben-Chen, Adrian Butscher, Justin Solomon, and Leonidas Guibas · 2010
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Kinectfusion: Real-time dense surface mapping and tracking
Richard A Newcombe, Shahram Izadi, Otmar Hilliges, David Molyneaux, David Kim, Andrew J Davison, Pushmeet Kohi, Jamie Shotton, Steve Hodges, and Andrew Fitzgibbon · 2011
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As-killing-as-possible vector fields for planar deformation
Justin Solomon, Mirela Ben-Chen, Adrian Butscher, and Leonidas J. Guibas · 2011
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On the velocity of an implicit surface
Jos Stam and Ryan Schmidt · 2011
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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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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Learning a predictable and generative vector representation for objects
Rohit Girdhar, David F Fouhey, Mikel Rodriguez, and Abhinav Gupta · 2016
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Near-isometric level set tracking
Michael Tao, Justin Solomon, and Adrian Butscher · 2016
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Multi-view 3d models from single images with a convolutional network
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
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Dynamic FAUST: Registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2017
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Dynamic FAUST: registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2017
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3d shape reconstruction from sketches via multi-view convolutional networks
Zhaoliang Lun, Matheus Gadelha, Evangelos Kalogerakis, Subhransu Maji, and Rui Wang · 2017
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Learning 3d object categories by looking around them
David Novotny, Diane Larlus, and Andrea Vedaldi · 2017
Cited alongside, same era.
Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
Cited alongside, same era.
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.
Killingfusion: Non-rigid 3d reconstruction without correspondences
Miroslava Slavcheva, Maximilian Baust, Daniel Cremers, and Slobodan Ilic · 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.
Learning representations and generative models for 3d point clouds
Occupancy flow: 4d reconstruction by learning particle dynamics
Michael Niemeyer, Lars M. Mescheder, Michael Oechsle, 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 Newcombe, and Steven Lovegrove · 2019
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3dn: 3d deformation network
Weiyue Wang, Duygu Ceylan, Radomir Mech, and Ulrich Neumann · 2019
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Deep geometric prior for surface reconstruction
Francis Williams, Teseo Schneider, Claudio Silva, Denis Zorin, Joan Bruna, and Daniele Panozzo · 2019
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Disn: Deep implicit surface network for high-quality single-view 3d reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, and Ulrich Neumann · 2019
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Sal: Sign agnostic learning of shapes from raw data
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Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 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.
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.
Matryoshka networks: Predicting 3d geometry via nested shape layers
Stephan R Richter and Stefan Roth · 2018
Cited alongside, same era.
Pixel2mesh: Generating 3d mesh models from single rgb images
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang · 2018
Cited alongside, same era.
Controlling neural level sets
Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, and Yaron Lipman · 2019
Cited alongside, same era.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Cited alongside, same era.
Matan Atzmon and Yaron Lipman · 2020
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Sald: Sign agnostic learning with derivatives
Matan Atzmon and Yaron Lipman · 2020
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Neural unsigned distance fields for implicit function learning
Julian Chibane, Gerard Pons-Moll, et al · 2020
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Limp: Learning latent shape representations with metric preservation priors
Luca Cosmo, Antonio Norelli, Oshri Halimi, Ron Kimmel, and Emanuele Rodolà · 2020
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Hamiltonian dynamics for real-world shape interpolation
Marvin Eisenberger and Daniel Cremers · 2020
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Local deep implicit functions for 3d shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, and Thomas Funkhouser · 2020
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Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
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Shapeflow: Learnable deformations among 3d shapes
Chiyu Jiang, Jingwei Huang, Andrea Tagliasacchi, Leonidas Guibas, et al · 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 Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
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Voronoinet: General functional approximators with local support
Francis Williams, Jerome Parent-Levesque, Derek Nowrouzezahrai, Daniele Panozzo, Kwang Moo Yi, and Andrea Tagliasacchi · 2020
Later among the works it cites.