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We present SP-GAN, a new unsupervised sphere-guided generative model for direct synthesis of 3D shapes in the form of point clouds.
3D ShapeNets: A deep representation for volumetric shapes. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 1912–1920
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ShapeNet: An information-rich 3D model repository
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SMPL: A skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J. Black. 2015 · 2015
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Density estimation using real NVP. In International Conference on Learning Representations (ICLR)
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio. 2016 · 2016
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Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling. In Conference on Neural Information Processing Systems (NeurIPS) . 82–90
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum. 2016 · 2016
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Dip transform for 3D shape reconstruction
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A learned representation for artistic style. In International Conference on Learning Representations (ICLR)
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Real-time geometry, albedo, and motion reconstruction using a single RGB-D camera
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Modeling surface appearance from a single photograph using self-augmented convolutional neural networks
Xiao Li, Yue Dong, Pieter Peers, and Xin Tong. 2017 · 2017
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Least squares generative adversarial networks. In IEEE International Conference on Computer Vision (ICCV) . 2794–2802
Xudong Mao, Qing Li, Haoran Xie, Raymond Y.K. Lau, Zhen Wang, and Stephen Paul Smolley. 2017 · 2017
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SurfNet: Generating 3D shape surfaces using deep residual networks. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 6040–6049
Ayan Sinha, Asim Unmesh, Qixing Huang, and Karthik Ramani. 2017 · 2017
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Improved adversarial systems for 3D object generation and reconstruction. In Conference on Robot Learning . PMLR, 87–96
Edward J. Smith and David Meger. 2017 · 2017
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Virtual rephotography: Novel view prediction error for 3D reconstruction
Michael Waechter, Mate Beljan, Simon Fuhrmann, Nils Moehrle, Johannes Kopf, and Michael Goesele. 2017 · 2017
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MarrNet: 3D shape reconstruction via 2.5D sketches. In Conference on Neural Information Processing Systems (NeurIPS) . 540–550
Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, Bill Freeman, and Josh Tenenbaum. 2017 · 2017
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Silvia Zuffi, Angjoo Kanazawa, David Jacobs, and Michael J. Black. 2017 · 2017
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Learning representations and generative models for 3D point clouds. In Proceedings of International Conference on Machine Learning (ICML) . 40–49
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J. Guibas. 2018 · 2018
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A papier-mâché approach to learning 3D surface generation. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 216–224
Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, and Mathieu Aubry. 2018 · 2018
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Image-to-voxel model translation with conditional adversarial networks. In European Conference on Computer Vision (ECCV)
Vladimir A. Knyaz, Vladimir V Kniaz, and Fabio Remondino. 2018 · 2018
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Pixel2Mesh: Generating 3D mesh models from single RGB images. In European Conference on Computer Vision (ECCV) . 52–67
Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang. 2018 · 2018
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Dense 3D object reconstruction from a single depth view
PointFlow: 3D point cloud generation with continuous normalizing flows. In IEEE International Conference on Computer Vision (ICCV) . 4541–4550
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan. 2019 · 2019
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LOGAN: Unpaired shape transform in latent overcomplete space
Kangxue Yin, Zhiqin Chen, Hui Huang, Daniel Cohen-Or, and Hao Zhang. 2019 · 2019
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DeepHuman: 3D human reconstruction from a single image. In IEEE International Conference on Computer Vision (ICCV) . 7739–7749
Zerong Zheng, Tao Yu, Yixuan Wei, Qionghai Dai, and Yebin Liu. 2019 · 2019
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A progressive conditional generative adversarial network for generating dense and colored 3D point clouds. In International Conference on 3D Vision (3DV)
Mohammad Samiul Arshad and William J. Beksi. 2020 · 2020
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Learning gradient fields for shape generation. In European Conference on Computer Vision (ECCV)
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Bo Yang, Stefano Rosa, Andrew Markham, Niki Trigoni, and Hongkai Wen. 2018 · 2018
Cited alongside, same era.
P2P-Net: Bidirectional point displacement net for shape transform
Kangxue Yin, Hui Huang, Daniel Cohen-Or, and Hao Zhang. 2018 · 2018
Cited alongside, same era.
PCN: Point completion network. In International Conference on 3D Vision (3DV) . 728–737
Wentao Yuan, Tejas Khot, David Held, Christoph Mertz, and Martial Hebert. 2018 · 2018
Cited alongside, same era.
Learning implicit fields for generative shape modeling. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 5939–5948
Zhiqin Chen and Hao Zhang. 2019 · 2019
Cited alongside, same era.
Composite shape modeling via latent space factorization. In IEEE International Conference on Computer Vision (ICCV) . 8140–8149
Anastasia Dubrovina, Fei Xia, Panos Achlioptas, Mira Shalah, Raphaël Groscot, and Leonidas J. Guibas. 2019 · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 4401–4410
Tero Karras, Samuli Laine, and Timo Aila. 2019 · 2019
Cited alongside, same era.
Occupancy networks: Learning 3D reconstruction in function space. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 4460–4470
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger. 2019 · 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 · 2019
Cited alongside, same era.
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan. 2020 · 2020
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MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement
Rinon Gal, Amit Bermano, Hao Zhang, and Daniel Cohen-Or. 2020 · 2020
Later among the works it cites.
Point2Mesh: A Self-Prior for Deformable Meshes
Rana Hanocka, Gal Metzer, Raja Giryes, and Daniel Cohen-Or. 2020 · 2020
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Progressive point cloud deconvolution generation network. In European Conference on Computer Vision (ECCV)
Le Hui, Rui Xu, Jin Xie, Jianjun Qian, and Jian Yang. 2020 · 2020
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SoftFlow: Probabilistic framework for normalizing flow on manifolds. In Conference on Neural Information Processing Systems (NeurIPS)
Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang, Joun Yeop Lee, and Nam Soo Kim. 2020 · 2020
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Discrete point flow networks for efficient point cloud generation. In European Conference on Computer Vision (ECCV)
Roman Klokov, Edmond Boyer, and Jakob Verbeek. 2020 · 2020
Later among the works it cites.
PT2PC: Learning to generate 3D point cloud shapes from part tree conditions. In European Conference on Computer Vision (ECCV)
Kaichun Mo, He Wang, Xinchen Yan, and Leonidas J. Guibas. 2020 · 2020
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A U-Net based discriminator for generative adversarial networks. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 8207–8216
Edgar Schonfeld, Bernt Schiele, and Anna Khoreva. 2020 · 2020
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PointGrow: Autoregressively learned point cloud generation with self-attention. In The IEEE Winter Conference on Applications of Computer Vision (WACV) . 61–70
Yongbin Sun, Yue Wang, Ziwei Liu, Joshua Siegel, and Sanjay Sarma. 2020 · 2020
Later among the works it cites.
PQ-NET: A generative part Seq2Seq network for 3D shapes. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 829–838
Rundi Wu, Yixin Zhuang, Kai Xu, Hao Zhang, and Baoquan Chen. 2020 · 2020
Later among the works it cites.
Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Yu Deng, Jiaolong Yang, and Xin Tong. 2021 · 2021
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Deep Implicit Moving Least-Squares Functions for 3D Reconstruction. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Shi-Lin Liu, Hao-Xiang Guo, Hao Pan, Pengshuai Wang, Xin Tong, and Yang Liu. 2021 · 2021
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