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We introduce CAPRI-Net, a neural network for learning compact and interpretable implicit representations of 3D computer-aided design (CAD) models, in the form of adaptive primitive assemblies.
Machine analysis of bubble chamber pictures
Paul VC Hough · 1959
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Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
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Surface reconstruction from unorganized points
Hugues Hoppe, Tony DeRose, Tom Duchamp, John McDonald, and Werner Stuetzle · 1992
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Reconstruction and representation of 3D objects with radial basis functions
J. C. Carr, R. K. Beatson, J. B. Cherrie, T. J. Mitchell, W. R. Fright, B. C. McCallum, and T. R. Evans · 2001
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On visual similarity based 3d model retrieval
Ding-Yun Chen, Xiao-Pei Tian, Yu-Te Shen, and Ming Ouhyoung · 2003
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Efficient hough transform for automatic detection of cylinders in point clouds
Tahir Rabbani and Frank Van Den Heuvel · 2005
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The Minimum Description Length Principle
Peter D. Grünwald · 2007
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Efficient ransac for point-cloud shape detection
Ruwen Schnabel, Roland Wahl, and Reinhard Klein · 2007
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The 3d hough transform for plane detection in point clouds: A review and a new accumulator design
Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter · 2011
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Characterizing structural relationships in scenes using graph kernels
Matthew Fisher, Manolis Savva, and Pat Hanrahan · 2011
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Globfit: Consistently fitting primitives by discovering global relations
Yangyan Li, Xiaokun Wu, Yiorgos Chrysathou, Andrei Sharf, Daniel Cohen-Or, and Niloy J Mitra · 2011
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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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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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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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Complementme: Weakly-supervised component suggestions for 3d modeling
Minhyuk Sung, Hao Su, Vladimir G Kim, Siddhartha Chaudhuri, and Leonidas Guibas · 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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Multi-view supervision for single-view reconstruction via differentiable ray consistency
Shubham Tulsiani, Tinghui Zhou, Alexei A Efros, and Jitendra Malik · 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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Inversecsg: Automatic conversion of 3d models to csg trees
Tao Du, Jeevana Priya Inala, Yewen Pu, Andrew Spielberg, Adriana Schulz, Daniela Rus, Armando Solar-Lezama, and Wojciech Matusik · 2018
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Atlasnet: A papier-mâché approach to learning 3d surface generation
Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan Russell, and Mathieu Aubry · 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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Csgnet: Neural shape parser for constructive solid geometry
Gopal Sharma, Rishabh Goyal, Difan Liu, Evangelos Kalogerakis, and Subhransu Maji · 2018
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Zhiqin Chen, Kangxue Yin, Matthew Fisher, Siddhartha Chaudhuri, and Hao Zhang · 2019
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Nasa: neural articulated shape approximation
Boyang Deng, JP Lewis, Timothy Jeruzalski, Gerard Pons-Moll, Geoffrey Hinton, Mohammad Norouzi, and Andrea Tagliasacchi · 2019
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Optimizing evolutionary csg tree extraction
Markus Friedrich, Pierre-Alain Fayolle, Thomas Gabor, and Claudia Linnhoff-Popien · 2019
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Sdm-net: Deep generative network for structured deformable mesh
Learning continuous image representation with local implicit image function
Yinbo Chen, Sifei Liu, and Xiaolong Wang · 2020
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Bsp-net: Generating compact meshes vis binary space partitioning
Zhiqin Chen, Andrea Tagliasacchi, and Hao Zhang · 2020
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Implicit functions in feature space for 3d shape reconstruction and completion
Julian Chibane, Thiemo Alldieck, and Gerard Pons-Moll · 2020
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Cvxnet: Learnable convex decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey Hinton, and Andrea Tagliasacchi · 2020
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Local implicit grid representations for 3d scenes
Chiyu Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, Thomas Funkhouser, et al · 2020
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Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, and Hao Zhang · 2019
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A survey of simple geometric primitives detection methods for captured 3d data
Adrien Kaiser, Jose Alonso Ybanez Zepeda, and Tamy Boubekeur · 2019
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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
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Supervised fitting of geometric primitives to 3d point clouds
Lingxiao Li, Minhyuk Sung, Anastasia Dubrovina, Li Yi, and Leonidas J Guibas · 2019
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Learning to infer implicit surfaces without 3d supervision
Shichen Liu, Shunsuke Saito, Weikai Chen, and Hao Li · 2019
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Occupancy networks: Learning 3D reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 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 J Guibas · 2019
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Yue Jiang, Dantong Ji, Zhizhong Han, and Matthias Zwicker · 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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Neural scene flow fields for space-time view synthesis of dynamic scenes
Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
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Deformable neural radiance fields
Keunhong Park, Utkarsh Sinha, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Steven M Seitz, and Ricardo-Martin Brualla · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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Parsenet: A parametric surface fitting network for 3d point clouds
Gopal Sharma, Difan Liu, Subhransu Maji, Evangelos Kalogerakis, Siddhartha Chaudhuri, and Radomír Měch · 2020
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Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien NP Martel, Alexander W Bergman, David B Lindell, and Gordon Wetzstein · 2020
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Adversarial generation of continuous images
Ivan Skorokhodov, Savva Ignatyev, and Mohamed Elhoseiny · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T Barron, and Ren Ng · 2020
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Fusion 360 gallery: A dataset and environment for programmatic cad reconstruction, 2020
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
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Space-time neural irradiance fields for free-viewpoint video
Wenqi Xian, Jia-Bin Huang, Johannes Kopf, and Changil Kim · 2020
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Generative models as distributions of functions
Emilien Dupont, Yee Whye Teh, and Arnaud Doucet · 2021
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