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Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power.
Marching cubes: A high resolution 3d surface construction algorithm
William E. Lorensen and Harvey E. Cline · 1987
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Reconstruction and representation of 3d objects with radial basis functions
Jonathan C. Carr, Richard K. Beatson, Jon B. Cherrie, Tim J. Mitchell, W. Richard Fright, Bruce C. McCallum, and Tim R. Evans · 2001
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Modelling with implicit surfaces that interpolate
Greg Turk and James F. O’Brien · 2002
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The space of human body shapes: reconstruction and parameterization from range scans
Brett Allen, Brian Curless, and Zoran Popovic · 2003
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Interpolating and approximating implicit surfaces from polygon soup
Chen Shen, James F. O’Brien, and Jonathan Richard Shewchuk · 2004
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SCAPE: shape completion and animation of people
Dragomir Anguelov, Praveen Srinivasan, Daphne Koller, Sebastian Thrun, Jim Rodgers, and James Davis · 2005
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Completion and reconstruction with primitive shapes
Ruwen Schnabel, Patrick Degener, and Reinhard Klein · 2009
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Joint shape segmentation with linear programming
Qi-Xing Huang, Vladlen Koltun, and Leonidas J. Guibas · 2011
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Globfit: consistently fitting primitives by discovering global relations
Yangyan Li, Xiaokun Wu, Yiorgos Chrysanthou, Andrei Sharf, Daniel Cohen-Or, and Niloy J. Mitra · 2011
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The stitched puppet: A graphical model of 3d human shape and pose
Silvia Zuffi and Michael J. Black · 2011
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Co-abstraction of shape collections
Mehmet Ersin Yümer and Levent Burak Kara · 2012
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Learning part-based templates from large collections of 3d shapes
Vladimir G. Kim, Wilmot Li, Niloy J. Mitra, Siddhartha Chaudhuri, Stephen DiVerdi, and Thomas A. Funkhouser · 2013
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Meta-representation of shape families
Noa Fish, Melinos Averkiou, Oliver van Kaick, Olga Sorkine-Hornung, Daniel Cohen-Or, and Niloy J. Mitra · 2014
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Shapenet: An information-rich 3d model repository
Angel X. Chang, Thomas A. Funkhouser, Leonidas J. Guibas, Pat Hanrahan, Qi-Xing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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SMPL: a skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Human pose estimation with iterative error feedback
João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, and Jitendra Malik · 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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Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J Guibas · 2017
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Dynamic FAUST: Registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2017
Earlier work this paper cites.
Hierarchical surface prediction for 3d object reconstruction
Christian Hane, Shubham Tulsiani, and Jitendra Malik · 2017
Earlier work this paper cites.
GRASS: generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao (Richard) Zhang, and Leonidas J. Guibas · 2017
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Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2017
Cited alongside, same era.
Learning shape abstractions by assembling volumetric primitives
Shubham Tulsiani, Hao Su, Leonidas J. Guibas, Alexei A. Efros, and Jitendra Malik · 2017
Cited alongside, same era.
Marrnet: 3d shape reconstruction via 2.5d sketches
Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, Bill Freeman, and Josh Tenenbaum · 2017
Cited alongside, same era.
Syncspeccnn: Synchronized spectral CNN for 3d shape segmentation
Li Yi, Hao Su, Xingwen Guo, and Leonidas J. Guibas · 2017
Cited alongside, same era.
3d-prnn: Generating shape primitives with recurrent neural networks
Chuhang Zou, Ersin Yumer, Jimei Yang, Duygu Ceylan, and Derek Hoiem · 2017
Cited alongside, same era.
Multi-chart generative surface modeling
Heli Ben-Hamu, Haggai Maron, Itay Kezurer, Gal Avineri, and Yaron Lipman · 2018
Supervised fitting of geometric primitives to 3d point clouds
Lingxiao Li, Minhyuk Sung, Anastasia Dubrovina, Li Yi, and Leonidas J. Guibas · 2019
Later among the works it cites.
PU-GAN: A point cloud upsampling adversarial network
Ruihui Li, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, and Pheng-Ann Heng · 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.
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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Superquadrics revisited: Learning 3d shape parsing beyond cuboids
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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.
Atlasnet: 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.
End-to-end recovery of human shape and pose
Angjoo Kanazawa, Michael J. Black, David W. Jacobs, and Jitendra Malik · 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.
Learning shape priors for single-view 3d completion and reconstruction
Jiajun Wu, Chengkai Zhang, Xiuming Zhang, Zhoutong Zhang, William T. Freeman, and Joshua B. Tenenbaum · 2018
Cited alongside, same era.
Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
Cited alongside, same era.
Despoina Paschalidou, Ali Osman Ulusoy, and Andreas Geiger · 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.
Pixel2mesh++: Multi-view 3d mesh generation via deformation
Chao Wen, Yinda Zhang, Zhuwen Li, and Yanwei Fu · 2019
Later among the works it cites.
DISN: deep implicit surface network for high-quality single-view 3d reconstruction
Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomír Mech, and Ulrich Neumann · 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
Later among the works it cites.
Detailed human shape estimation from a single image by hierarchical mesh deformation
Hao Zhu, Xinxin Zuo, Sen Wang, Xun Cao, and Ruigang Yang · 2019
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, Steven Lovegrove, and Richard Newcombe · 2020
Closest in time.
Deformed implicit field: Modeling 3d shapes with learned dense correspondence, 2020
Yu Deng, Jiaolong Yang, and Xin Tong · 2020
Closest in time.
Curriculum deepsdf, 2020
Yueqi Duan, Haidong Zhu, He Wang, Li Yi, Ram Nevatia, and Leonidas J. Guibas · 2020
Closest in time.
Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
Closest in time.
Dualsdf: Semantic shape manipulation using a two-level representation
Zekun Hao, Hadar Averbuch-Elor, Noah Snavely, and Serge Belongie · 2020
Closest in time.
Local implicit grid representations for 3d scenes
Chiyu Max Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, and Thomas A. Funkhouser · 2020
Closest in time.
Learning implicit functions for topology-varying dense 3d shape correspondence
Feng Liu and Xiaoming Liu · 2020
Closest in time.
Learning unsupervised hierarchical part decomposition of 3d objects from a single rgb image
Despoina Paschalidou, Luc Gool, and Andreas Geiger · 2020
Closest in time.
PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations
Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Carsten Stoll, and Christian Theobalt · 2020
Closest in time.
Keypointnet: A large-scale 3d keypoint dataset aggregated from numerous human annotations
Yang You, Yujing Lou, Chengkun Li, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Cewu Lu, and Weiming Wang · 2020
Closest in time.