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Deep generative models of 3D shapes have received a great deal of research interest.
Edge-based data structures for solid modeling in curved-surface environments
K. Weiler · 1985
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Topological structures for geometric modeling
Kevin Weiler · 1986
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Adam: A method for stochastic optimization, 2014
Diederik P. Kingma and Jimmy Ba · 2014
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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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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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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 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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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Pixelcnn++: A pixelcnn implementation with discretized logistic mixture likelihood and other modifications
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P. Kingma · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Learning representations and generative models for 3D point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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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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Deep marching cubes: Learning explicit surface representations
Yiyi Liao, Simon Donne, and Andreas Geiger · 2018
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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 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
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.
Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
Cited alongside, same era.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Cited alongside, same era.
Abc: A big cad model dataset for geometric deep learning
Sebastian Koch, Albert Matveev, Zhongshi Jiang, Francis Williams, Alexey Artemov, Evgeny Burnaev, Marc Alexa, Denis Zorin, and Daniele Panozzo · 2019
Cited alongside, same era.
Rwth asr systems for librispeech: Hybrid vs attention
Christoph Lüscher, Eugen Beck, Kazuki Irie, Markus Kitza, Wilfried Michel, Albert Zeyer, Ralf Schlüter, and Hermann Ney · 2019
Uv-net: Learning from curve-networks and solids
Pradeep Kumar Jayaraman, Aditya Sanghi, Joseph Lambourne, Thomas Davies, Hooman Shayani, and Nigel Morris · 2020
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Shapeassembly: Learning to generate programs for 3d shape structure synthesis
R. Kenny Jones, Theresa Barton, Xianghao Xu, Kai Wang, Ellen Jiang, Paul Guerrero, Niloy J. Mitra, and Daniel Ritchie · 2020
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Ucsg-net–unsupervised discovering of constructive solid geometry tree
Kacper Kania, Maciej Zięba, and Tomasz Kajdanowicz · 2020
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Sketch2cad: Sequential cad modeling by sketching in context
Changjian Li, Hao Pan, Adrien Bousseau, and Niloy J. Mitra · 2020
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PolyGen: An autoregressive generative model of 3D meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, and Peter Battaglia · 2020
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Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas J Guibas · 2019
Cited alongside, same era.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Cited alongside, same era.
Learning to infer and execute 3d shape programs
Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T Freeman, Joshua B Tenenbaum, and Jiajun Wu · 2019
Cited alongside, same era.
Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
Cited alongside, same era.
Learning gradient fields for shape generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan · 2020
Cited alongside, same era.
Parsenet: A parametric surface fitting network for 3d point clouds
Gopal Sharma, Difan Liu, Subhransu Maji, Evangelos Kalogerakis, Siddhartha Chaudhuri, and Radomír Měch · 2020
Later among the works it cites.
Learning to infer shape programs using latent execution self training
Homer Walke, R Kenny Jones, and Daniel Ritchie · 2020
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Pie-net: Parametric inference of point cloud edges
Xiaogang Wang, Yuelang Xu, Kai Xu, Andrea Tagliasacchi, Bin Zhou, Ali Mahdavi-Amiri, and Hao Zhang · 2020
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Sceneformer: Indoor scene generation with transformers
Xinpeng Wang, Chandan Yeshwanth, and Matthias Nießner · 2020
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Fusion 360 gallery: A dataset and environment for programmatic cad reconstruction
Karl D. D. Willis, Yewen Pu, Jieliang Luo, Hang Chu, Tao Du, Joseph G. Lambourne, Armando Solar-Lezama, and Wojciech Matusik · 2020
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Pq-net: A generative part seq2seq network for 3d shapes
Rundi Wu, Yixin Zhuang, Kai Xu, Hao Zhang, and Baoquan Chen · 2020
Later among the works it cites.
Computer-aided design as language
Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, and Stefano Saliceti · 2021
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Brepnet: A topological message passing system for solid models
Joseph G Lambourne, Karl DD Willis, Pradeep Kumar Jayaraman, Aditya Sanghi, Peter Meltzer, and Hooman Shayani · 2021
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Sketchgen: Generating constrained cad sketches
Wamiq Reyaz Para, Shariq Farooq Bhat, Paul Guerrero, Tom Kelly, Niloy Mitra, Leonidas Guibas, and Peter Wonka · 2021
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Engineering sketch generation for computer-aided design
Karl DD Willis, Pradeep Kumar Jayaraman, Joseph G Lambourne, Hang Chu, and Yewen Pu · 2021
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Inferring cad modeling sequences using zone graphs
Xianghao Xu, Wenzhe Peng, Chin-Yi Cheng, Karl DD Willis, and Daniel Ritchie · 2021
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