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We present ShapeFormer, a transformer-based network that produces a distribution of object completions, conditioned on incomplete, and possibly noisy, point clouds.
The ball-pivoting algorithm for surface reconstruction
Fausto Bernardini, Joshua Mittleman, Holly Rushmeier, Claudio Silva, and Gabriel Taubin · 1999
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Yoshua Bengio and Samy Bengio · 2000
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Poisson surface reconstruction
Michael Kazhdan, Matthew Bolitho, and Hugues Hoppe · 2006
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Multi-view stereo: A tutorial
Yasutaka Furukawa and Carlos Hernández · 2013
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Screened poisson surface reconstruction
Michael Kazhdan and Hugues Hoppe · 2013
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Shapenet: An information-rich 3d model repository, 2015
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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Made: Masked autoencoder for distribution estimation
Mathieu Germain, Karol Gregor, Iain Murray, and Hugo Larochelle · 2015
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Completing 3d object shape from one depth image
Jason Rock, Tanmay Gupta, Justin Thorsen, JunYoung Gwak, Daeyun Shin, and Derek Hoiem · 2015
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A large dataset of object scans, 2016
Sungjoon Choi, Qian-Yi Zhou, Stephen Miller, and Vladlen Koltun · 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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3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Conditional image generation with pixelcnn decoders
Aäron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, and Koray Kavukcuoglu · 2016
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Neural autoregressive distribution estimation
Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, and Hugo Larochelle · 2016
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Pixel recurrent neural networks
Aaron Van Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Learning representations and generative models for 3D point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J. Guibas · 2017
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A survey of surface reconstruction from point clouds
Matthew Berger, Andrea Tagliasacchi, Lee M Seversky, Pierre Alliez, Gael Guennebaud, Joshua A Levine, Andrei Sharf, and Claudio T Silva · 2017
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Dynamic FAUST: Registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
R. Qi Charles, Hao Su, Mo Kaichun, and Leonidas J. Guibas · 2017
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Shape completion using 3D-Encoder-Predictor CNNs and shape synthesis
Angela Dai, Charles Ruizhongtai Qi, and Matthias NieBner · 2017
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A point set generation network for 3D object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas Guibas · 2017
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Hierarchical surface prediction for 3d object reconstruction
Christian Häne, Shubham Tulsiani, and Jitendra Malik · 2017
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Neural discrete representation learning
Aäron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Pixelsnail: An improved autoregressive generative model
Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, and Pieter Abbeel · 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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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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Deformable shape completion with graph convolutional autoencoders, 2018
Or Litany, Alex Bronstein, Michael Bronstein, and Ameesh Makadia · 2018
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Generating wikipedia by summarizing long sequences, 2018
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer · 2018
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Image transformer
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Learning 3d shape completion from laser scan data with weak supervision
David Stutz and Andreas Geiger · 2018
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Pixel2mesh: Generating 3d mesh models from single rgb images, 2018
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang · 2018
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Pcn: Point completion network
Wentao Yuan, Tejas Khot, David Held, Christoph Mertz, and Martial Hebert · 2018
Taming transformers for high-resolution image synthesis, 2020
Patrick Esser, Robin Rombach, and Björn Ommer · 2020
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Local deep implicit functions for 3d shape
Kyle Genova, F. Cole, Avneesh Sud, Aaron Sarna, and T. Funkhouser · 2020
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Local implicit grid representations for 3d scenes
Chiyu Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, and Thomas Funkhouser · 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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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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Pointgrow: Autoregressively learned point cloud generation with self-attention
Yongbin Sun, Yue Wang, Ziwei Liu, Joshua Siegel, and Sanjay Sarma · 2020
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Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Hierarchical autoregressive image models with auxiliary decoders
J. Fauw, S. Dieleman, and K. Simonyan · 2019
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Image-based 3d object reconstruction: State-of-the-art and trends in the deep learning era
Xian-Feng Han, Hamid Laga, and Mohammed Bennamoun · 2019
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Axial attention in multidimensional transformers, 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 2019
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Variational implicit point set surfaces
Zhiyang Huang, Nathan Carr, and Tao Ju · 2019
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Sceneformer: Indoor scene generation with transformers
Xinpeng Wang, Chandan Yeshwanth, and Matthias Nießner · 2020
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Multimodal shape completion via conditional generative adversarial networks
Rundi Wu, Xuelin Chen, Yixin Zhuang, and Baoquan Chen · 2020
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Multimodal shape completion via imle
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Beit: Bert pre-training of image transformers, 2021
Hangbo Bao, Li Dong, and Furu Wei · 2021
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Multiresolution deep implicit functions for 3d shape representation
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Rethinking attention with performers, 2021
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy Colwell, and Adrian Weller · 2021
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Variable-rate discrete representation learning
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Masked autoencoders are scalable vision learners, 2021
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2021
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Parallel and flexible sampling from autoregressive models via langevin dynamics, 2021
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Deep implicit moving least-squares functions for 3d reconstruction
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Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, and Peter W Battaglia · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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High-fidelity pluralistic image completion with transformers
Ziyu Wan, Jingbo Zhang, Dongdong Chen, and Jing Liao · 2021
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Snowflakenet: Point cloud completion by snowflake point deconvolution with skip-transformer
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Pointr: Diverse point cloud completion with geometry-aware transformers
Xumin Yu, Yongming Rao, Ziyi Wang, Zuyan Liu, Jiwen Lu, and Jie Zhou · 2021
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Point-bert: Pre-training 3d point cloud transformers with masked point modeling
Xumin Yu, Lulu Tang, Yongming Rao, Tiejun Huang, Jie Zhou, and Jiwen Lu · 2021
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Unsupervised 3d shape completion through gan inversion
Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, and Chen Change Loy · 2021
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3d shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 2021
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Autosdf: Shape priors for 3d completion, reconstruction and generation
Paritosh Mittal, Y. Cheng, Maneesh Singh, and Shubham Tulsiani · 2022
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