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Human perception of 3D shapes goes beyond reconstructing them as a set of points or a composition of geometric primitives: we also effortlessly understand higher-level shape structure such as the repetition and reflective symmetry of object parts.
Machine perception of three-dimensional solids
Lawrence G Roberts · 1963
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Visual perception by computer
Thomas O Binford · 1971
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Parametric correspondence and chamfer matching: Two new techniques for image matching
Harry G Barrow, Jay M Tenenbaum, Robert C Bolles, and Helen C Wolf · 1977
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Recognition-by-components: a theory of human image understanding
Irving Biederman · 1987
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The earth mover’s distance as a metric for image retrieval
Yossi Rubner, Carlo Tomasi, and Leonidas J Guibas · 2000
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Z3: An efficient smt solver
Leonardo De Moura and Nikolaj Bjørner · 2008
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Inverse procedural modeling by automatic generation of l-systems
Ondrej Št’ava, Bedrich Beneš, Radomir Měch, Daniel G Aliaga, and Peter Krištof · 2010
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Probabilistic reasoning for assembly-based 3d modeling
Siddhartha Chaudhuri, Evangelos Kalogerakis, Leonidas Guibas, and Vladlen Koltun · 2011
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Mirror-image sensitivity and invariance in object and scene processing pathways
Daniel D Dilks, Joshua B Julian, Jonas Kubilius, Elizabeth S Spelke, and Nancy Kanwisher · 2011
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Comparing machines and humans on a visual categorization test
François Fleuret, Ting Li, Charles Dubout, Emma K Wampler, Steven Yantis, and Donald Geman · 2011
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Principles of Gestalt psychology
Kurt Koffka · 2013
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Structure-aware shape processing
Niloy Mitra, Michael Wand, Hao Richard Zhang, Daniel Cohen-Or, Vladimir Kim, and Qi-Xing Huang · 2013
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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Unsupervised learning by program synthesis
Kevin Ellis, Armando Solar-Lezama, and Josh Tenenbaum · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Part-based modelling of compound scenes from images
Anton van den Hengel, Chris Russell, Anthony Dick, John Bastian, Daniel Pooley, Lachlan Fleming, and Lourdes Agapito · 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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Terpret: A probabilistic programming language for program induction
Alexander L Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, and Daniel Tarlow · 2016
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Interactive sketching of urban procedural models
Gen Nishida, Ignacio Garcia-Dorado, Daniel G Aliaga, Bedrich Benes, and Adrien Bousseau · 2016
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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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Retrieval on parametric shape collections
Adriana Schulz, Ariel Shamir, Ilya Baran, David IW Levin, Pitchaya Sitthi-Amorn, and Wojciech Matusik · 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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MarrNet: 3D Shape Reconstruction via 2.5D Sketches
Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, William T Freeman, and Joshua B Tenenbaum · 2017
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3d-prnn: Generating shape primitives with recurrent neural networks
Chuhang Zou, Ersin Yumer, Jimei Yang, Duygu Ceylan, and Derek Hoiem · 2017
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Learning to infer graphics programs from hand-drawn imatges
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Scott Reed and Nando De Freitas · 2016
Cited alongside, same era.
Neurally-guided procedural models: Amortized inference for procedural graphics programs using neural networks
Daniel Ritchie, Anna Thomas, Pat Hanrahan, and Noah Goodman · 2016
Cited alongside, same era.
Deepcoder: Learning to write programs
Matej Balog, Alexander L Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow · 2017
Cited alongside, same era.
Programming with a differentiable forth interpreter
Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky, and Sebastian Riedel · 2017
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Making neural programming architectures generalize via recursion
Jonathon Cai, Richard Shin, and Dawn Song · 2017
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Robustfill: Neural program learning under noisy i/o
Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, and Pushmeet Kohli · 2017
Cited alongside, same era.
Inferring and executing programs for visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
Cited alongside, same era.
Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, and Joshua B Tenenbaum · 2018
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Synthesizing programs for images using reinforced adversarial learning
Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, SM Eslami, and Oriol Vinyals · 2018
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Physical primitive decomposition
Zhijian Liu, William T Freeman, Joshua B Tenenbaum, and Jiajun Wu · 2018
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Procedural modeling of a building from a single image
Gen Nishida, Adrien Bousseau, and Daniel G Aliaga · 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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Scores: Shape composition with recursive substructure priors
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Renjiao Yi, and Hao Zhang · 2018
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Learning to describe scenes with programs
Yunchao Liu, Zheng Wu, Daniel Ritchie, William T Freeman, Joshua B Tenenbaum, and Jiajun Wu · 2019
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