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Abstracting complex 3D shapes with parsimonious part-based representations has been a long standing goal in computer vision.
Machine perception of three-dimensional solids
Peter Elias and Lawrence G Roberts · 1963
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Visual perception by computer
I Binford · 1971
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Superquadrics and angle-preserving transformations
Alan H Barr · 1981
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Human image understanding: Recent research and a theory
Irving Biederman · 1986
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Constructive solid geometry for polyhedral objects
David H Laidlaw, W Benjamin Trumbore, and John F Hughes · 1986
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Parts: Structured descriptions of shape
Alex Pentland · 1986
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Learning representations by back-propagating errors
David E. Rumelhart, Geoffrey E. Hinton, and Ronald J. Williams · 1986
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Recognition-by-components: a theory of human image understanding
Irving Biederman · 1987
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Recovery of parametric models from range images: The case for superquadrics with global deformations
Franc Solina and Ruzena Bajcsy · 1990
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Dynamic 3d models with local and global deformations: deformable superquadrics
Demetri Terzopoulos and Dimitris N. Metaxas · 1990
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams · 1992
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Volumetric models in computer vision-an overview
Franc Solina · 1994
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Equal-distance sampling of supercllipse models
Maurizio Pilu and Robert B. Fisher · 1995
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Segmentation and Recovery of Superquadrics
Ales Jaklic, Ales Leonardis, and Franc Solina · 2000
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Segmentation and superquadric modeling of 3d objects
Laurent Chevalier, Fabrice Jaillet, and Atilla Baskurt · 2003
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Concurrent multiple instance learning for image categorization
G.J. Qi, X.S. Hua, Y. Rui, T. Mei, J. Tang, and H.J. Zhang · 2007
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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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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 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-r2n2: A unified approach for single and multi-view 3d object reconstruction
Christopher Bongsoo Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese · 2016
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Learning a predictable and generative vector representation for objects
Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
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Learning shape abstractions by assembling volumetric primitives
Shubham Tulsiani, Hao Su, Leonidas J. Guibas, Alexei A. Efros, and Jitendra Malik · 2017
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Learning from synthetic humans
Gül Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J. Black, Ivan Laptev, and Cordelia Schmid · 2017
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Revisiting superquadric fitting: A numerically stable formulation
Narunas Vaskevicius and Andreas Birk · 2017
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3d-prnn: Generating shape primitives with recurrent neural networks
C. Zou, E. Yumer, J. Yang, D. Ceylan, and D. Hoiem · 2017
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Learning to infer graphics programs from hand-drawn images
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Rohit Girdhar, David F. Fouhey, Mikel Rodriguez, and Abhinav Gupta · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Unsupervised learning of 3d structure from images
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, and Nicolas Heess · 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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A point set generation network for 3d object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J. Guibas · 2017
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Hierarchical surface prediction for 3d object reconstruction
Christian Häne, Shubham Tulsiani, and Jitendra Malik · 2017
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Learned multi-patch similarity
Wilfried Hartmann, Silvano Galliani, Michal Havlena, Luc Van Gool, and Konrad Schindler · 2017
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Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, and Joshua B. Tenenbaum · 2018
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AtlasNet: A papier-mâché approach to learning 3d surface generation
Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, and Mathieu Aubry · 2018
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Deepmvs: Learning multi-view stereopsis
Po-Han Huang, Kevin Matzen, Johannes Kopf, Narendra Ahuja, and Jia-Bin Huang · 2018
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Deep marching cubes: Learning explicit surface representations
Yiyi Liao, Simon Donne, and Andreas Geiger · 2018
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Im2struct: Recovering 3d shape structure from a single RGB image
Chengjie Niu, Jun Li, and Kai Xu · 2018
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Raynet: Learning volumetric 3d reconstruction with ray potentials
Despoina Paschalidou, Ali Osman Ulusoy, Carolin Schmitt, Luc van Gool, and Andreas Geiger · 2018
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Csgnet: Neural shape parser for constructive solid geometry
Gopal Sharma, Rishabh Goyal, Difan Liu, Evangelos Kalogerakis, and Subhransu Maji · 2018
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Pixel2mesh: Generating 3d mesh models from single rgb images
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang · 2018
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Mvsnet: Depth inference for unstructured multi-view stereo
Yao Yao, Zixin Luo, Shiwei Li, Tian Fang, and Long Quan · 2018
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