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We present a novel neural network architecture, termed Decomposer-Composer, for semantic structure-aware 3D shape modeling.
Fast approximate energy minimization via graph cuts
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An optimization approach to improving collections of shape maps
Andy Nguyen, Mirela Ben-Chen, Katarzyna Welnicka, Yinyu Ye, and Leonidas Guibas · 2011
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Photo-inspired model-driven 3d object modeling
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Evangelos Kalogerakis, Siddhartha Chaudhuri, Daphne Koller, and Vladlen Koltun · 2012
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Chao-Hui Shen, Hongbo Fu, Kang Chen, and Shi-Min Hu · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Image co-segmentation via consistent functional maps
Fan Wang, Qixing Huang, and Leonidas J Guibas · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Projection based transfer learning
Christian Poelitz · 2014
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Shapenet: An information-rich 3d model repository
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Spatial transformer networks
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Tensorflow: a system for large-scale machine learning
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 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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beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2016
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Learning 3d deformation of animals from 2d images
Angjoo Kanazawa, Shahar Kovalsky, Ronen Basri, and David Jacobs · 2016
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Generative image modeling using style and structure adversarial networks
Xiaolong Wang and Abhinav Gupta · 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 a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T Freeman, and Joshua B Tenenbaum · 2016
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Predictive and generative neural networks for object functionality
Ruizhen Hu, Zihao Yan, Jingwen Zhang, Oliver van Kaick, Ariel Shamir, Hao Zhang, and Hui Huang · 2018
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Deformnet: Free-form deformation network for 3d shape reconstruction from a single image
Andrey Kurenkov, Jingwei Ji, Animesh Garg, Viraj Mehta, JunYoung Gwak, Christopher Choy, and Silvio Savarese · 2018
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Pointgrid: A deep network for 3d shape understanding
Truc Le and Ye Duan · 2018
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St-gan: Spatial transformer generative adversarial networks for image compositing
Chen-Hsuan Lin, Ersin Yumer, Oliver Wang, Eli Shechtman, and Simon Lucey · 2018
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Dual-domain calibration transfer using orthogonal projection
Dominic V Poerio and Steven D Brown · 2018
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Ganimation: Anatomically-aware facial animation from a single image
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A scalable active framework for region annotation in 3d shape collections
Li Yi, Vladimir G Kim, Duygu Ceylan, I Shen, Mengyan Yan, Hao Su, Cewu Lu, Qixing Huang, Alla Sheffer, Leonidas Guibas, et al · 2016
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Representation learning and adversarial generation of 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2017
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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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Grass: Generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, and Leonidas Guibas · 2017
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The shape variational autoencoder: A deep generative model of part-segmented 3d objects
Charlie Nash and Chris KI Williams · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Octnet: Learning deep 3d representations at high resolutions
Gernot Riegler, Ali Osman Ulusoy, and Andreas Geiger · 2017
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Albert Pumarola, Antonio Agudo, Aleix M Martinez, Alberto Sanfeliu, and Francesc Moreno-Noguer · 2018
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Learning to generate the” unseen” via part synthesis and composition
Nadav Schor, Oren Katzir, Hao Zhang, and Daniel Cohen-Or · 2018
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Semantic structure and interpretability of word embeddings
Lutfi Kerem Senel, Ihsan Utlu, Veysel Yucesoy, Aykut Koc, and Tolga Cukur · 2018
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Deforming autoencoders: Unsupervised disentangling of shape and appearance, 2018
Zhixin Shu, Mihir Sahasrabudhe, Alp Guler, Dimitris Samaras, Nikos Paragios, and Iasonas Kokkinos · 2018
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Global-to-local generative model for 3d shapes
Hao Wang, Nadav Schor, Ruizhen Hu, Haibin Huang, Daniel Cohen-Or, and Hui Huang · 2018
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Structure-aware generative network for 3d-shape modeling
Zhijie Wu, Xiang Wang, Di Lin, Dani Lischinski, Daniel Cohen-Or, and Hui Huang · 2018
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Gibson env: Real-world perception for embodied agents
Fei Xia, Amir R Zamir, Zhiyang He, Alexander Sax, Jitendra Malik, and Silvio Savarese · 2018
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ShapeGlot: Learning language for shape differentiation
Panos Achlioptas, Judy Fan, X.D. Robert Hawkins, D. Noah Goodman, and J. Leonidas Guibas · 2019
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Learning part generation and assembly for structure-aware shape synthesis
Jun Li, Chengjie Niu, and Kai Xu · 2019
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Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas Guibas · 2019
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Sagnet: Structure-aware generative network for 3d-shape modeling
Zhijie Wu, Xiang Wang, Di Lin, Dani Lischinski, Daniel Cohen-Or, and Hui Huang · 2019
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