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We present TetGAN, a convolutional neural network designed to generate tetrahedral meshes.
A procedural approach to authoring solid models
Barbara Cutler, Julie Dorsey, Leonard McMillan, Matthias Müller, and Robert Jagnow · 2002
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Simplification of unstructured tetrahedral meshes by point sampling
Dirce Uesu, Louis Bavoil, Shachar Fleishman, Jason Shepherd, and Cláudio T Silva · 2005
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Bounded biharmonic weights for real-time deformation
Alec Jacobson, Ilya Baran, Jovan Popovic, and Olga Sorkine · 2011
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Active co-analysis of a set of shapes
Yunhai Wang, Shmulik Asafi, Oliver Van Kaick, Hao Zhang, Daniel Cohen-Or, and Baoquan Chen · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Auto-Encoding Variational Bayes
Diederik P. Kingma and Max Welling · 2014
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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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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Dihedral angle-based maps of tetrahedral meshes
Gilles-Philippe Paillé, Nicolas Ray, Pierre Poulin, Alla Sheffer, and Bruno Lévy · 2015
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TetGen, a Delaunay-based quality tetrahedral mesh generator
Hang Si · 2015
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Linear subspace design for real-time shape deformation
Yu Wang, Alec Jacobson, Jernej Barbič, and Ladislav Kavan · 2015
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Precomputed real-time texture synthesis with Markovian generative adversarial networks
Chuan Li and Michael Wand · 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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Improved training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 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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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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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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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
Cited alongside, same era.
Tetrahedral meshing in the wild
Yixin Hu, Qingnan Zhou, Xifeng Gao, Alec Jacobson, Denis Zorin, and Daniele Panozzo · 2018
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Robust watertight manifold surface generation method for ShapeNet models
Jingwei Huang, Hao Su, and Leonidas Guibas · 2018
Cited alongside, same era.
Rdcgan: Unsupervised representation learning with regularized deep convolutional generative adversarial networks
Mehran Mehralian and Babak Karasfi · 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.
Neural subdivision
Hsueh-Ti Derek Liu, Vladimir G Kim, Siddhartha Chaudhuri, Noam Aigerman, and Alec Jacobson · 2020
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Primal-dual mesh convolutional neural networks
Francesco Milano, Antonio Loquercio, Antoni Rosinol, Davide Scaramuzza, and Luca Carlone · 2020
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Polygen: An autoregressive generative model of 3D meshes
Charlie Nash, Yaroslav Ganin, SM Ali Eslami, and Peter Battaglia · 2020
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Monte carlo geometry processing: A grid-free approach to PDE-based methods on volumetric domains
Rohan Sawhney and Keenan Crane · 2020
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PointTriNet: Learned triangulation of 3D point sets
Nicholas Sharp and Maks Ovsjanikov · 2020
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COALESCE: Component assembly by learning to synthesize connections
Kangxue Yin, Zhiqin Chen, Siddhartha Chaudhuri, Matthew Fisher, Vladimir G Kim, and Hao Zhang · 2020
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Zhiqin Chen and Hao Zhang · 2019
Cited alongside, same era.
Sdm-net: Deep generative network for structured deformable mesh
Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, and Hao Zhang · 2019
Cited alongside, same era.
MeshCNN: a network with an edge
Rana Hanocka, Amir Hertz, Noa Fish, Raja Giryes, Shachar Fleishman, and Daniel Cohen-Or · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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.
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.
Bsp-net: Generating compact meshes via binary space partitioning
Zhiqin Chen, Andrea Tagliasacchi, and Hao Zhang · 2020
Cited alongside, same era.
Later among the works it cites.
DECOR-GAN: 3D shape detailization by conditional refinement
Zhiqin Chen, Vladimir G Kim, Matthew Fisher, Noam Aigerman, Hao Zhang, and Siddhartha Chaudhuri · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Subdivision-based mesh convolution networks
Shi-Min Hu, Zheng-Ning Liu, Meng-Hao Guo, Jun-Xiong Cai, Jiahui Huang, Tai-Jiang Mu, and Ralph R. Martin · 2021
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gradSim: Differentiable simulation for system identification and visuomotor control
Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jerome Parent-Levesque, Kevin Xie, Kenny Erleben, et al · 2021
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Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
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Neural parts: Learning expressive 3D shape abstractions with invertible neural networks
Despoina Paschalidou, Angelos Katharopoulos, Andreas Geiger, and Sanja Fidler · 2021
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Shape as points: A differentiable Poisson solver
Songyou Peng, Chiyu ”Max” Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, and Andreas Geiger · 2021
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Differentiable surface triangulation
Marie-Julie Rakotosaona, Noam Aigerman, Niloy J Mitra, Maks Ovsjanikov, and Paul Guerrero · 2021
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Deep marching tetrahedra: a hybrid representation for high-resolution 3D shape synthesis
Tianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu, and Sanja Fidler · 2021
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The shape matching element method: Direct animation of curved surface models
Ty Trusty, Honglin Chen, and David I.W. Levin · 2021
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Extracting Triangular 3D Models, Materials, and Lighting From Images
Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Mueller, and Sanja Fidler · 2022
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