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Generating 3D point clouds is challenging yet highly desired.
On visual similarity based 3d model retrieval
D.-Y. Chen, X.-P. Tian, Y.-T. Shen, and M. Ouhyoung · 2003
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Rotation invariant spherical harmonic representation of 3 d shape descriptors
M. Kazhdan, T. Funkhouser, and S. Rusinkiewicz · 2003
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Learning to combine foveal glimpses with a third-order boltzmann machine
H. Larochelle and G. E. Hinton · 2010
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Learning where to attend with deep architectures for image tracking
M. Denil, L. Bazzani, H. Larochelle, and N. de Freitas · 2012
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Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2013
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Neural machine translation by jointly learning to align and translate
D. Bahdanau, K. Cho, and Y. Bengio · 2014
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Beyond pascal: A benchmark for 3d object detection in the wild
Y. Xiang, R. Mottaghi, and S. Savarese · 2014
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Shapenet: An information-rich 3d model repository
A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, et al · 2015
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Geodesic convolutional neural networks on riemannian manifolds
J. Masci, D. Boscaini, M. Bronstein, and P. Vandergheynst · 2015
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Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
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3d shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
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Learning shape correspondence with anisotropic convolutional neural networks
D. Boscaini, J. Masci, E. Rodolà, and M. Bronstein · 2016
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Generative and discriminative voxel modeling with convolutional neural networks
A. Brock, T. Lim, J. M. Ritchie, and N. Weston · 2016
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Long short-term memory-networks for machine reading
J. Cheng, L. Dong, and M. Lapata · 2016
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3d-r2n2: A unified approach for single and multi-view 3d object reconstruction
C. B. Choy, D. Xu, J. Gwak, K. Chen, and S. Savarese · 2016
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Learning a predictable and generative vector representation for objects
R. Girdhar, D. F. Fouhey, M. Rodriguez, and A. Gupta · 2016
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Pixel recurrent neural networks
A. v. d. Oord, N. Kalchbrenner, and K. Kavukcuoglu · 2016
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Vconv-dae: Deep volumetric shape learning without object labels
A. Sharma, O. Grau, and M. Fritz · 2016
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Wavenet: A generative model for raw audio
A. Van Den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. W. Senior, and K. Kavukcuoglu · 2016
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Conditional image generation with pixelcnn decoders
A. van den Oord, N. Kalchbrenner, L. Espeholt, O. Vinyals, A. Graves, et al · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, B. Freeman, and J. Tenenbaum · 2016
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Representation learning and adversarial generation of 3d point clouds
P. Achlioptas, O. Diamanti, I. Mitliagkas, and L. Guibas · 2017
Cited alongside, same era.
A point set generation network for 3d object reconstruction from a single image
H. Fan, H. Su, and L. J. Guibas · 2017
Cited alongside, same era.
Shape generation using spatially partitioned point clouds
M. Gadelha, S. Maji, and R. Wang · 2017
Cited alongside, same era.
Submanifold sparse convolutional networks
B. Graham and L. van der Maaten · 2017
Cited alongside, same era.
Hierarchical surface prediction for 3d object reconstruction
C. Häne, S. Tulsiani, and J. Malik · 2017
Cited alongside, same era.
Variational autoencoders for deforming 3d mesh models
Q. Tan, L. Gao, Y.-K. Lai, and S. Xia · 2017
Later among the works it cites.
Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
Later among the works it cites.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Later among the works it cites.
O-cnn: Octree-based convolutional neural networks for 3d shape analysis
P.-S. Wang, Y. Liu, Y.-X. Guo, C.-Y. Sun, and X. Tong · 2017
Later among the works it cites.
Syncspeccnn: Synchronized spectral cnn for 3d shape segmentation
L. Yi, H. Su, X. Guo, and L. J. Guibas · 2017
Later among the works it cites.
Learning representations and generative models for 3d point clouds
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
Cited alongside, same era.
Escape from cells: Deep kd-networks for the recognition of 3d point cloud models
R. Klokov and V. Lempitsky · 2017
Cited alongside, same era.
Using locally corresponding cad models for dense 3d reconstructions from a single image
C. Kong, C.-H. Lin, and S. Lucey · 2017
Cited alongside, same era.
Learning efficient point cloud generation for dense 3d object reconstruction
C.-H. Lin, C. Kong, and S. Lucey · 2017
Cited alongside, same era.
Parallel wavenet: Fast high-fidelity speech synthesis
A. v. d. Oord, Y. Li, I. Babuschkin, K. Simonyan, O. Vinyals, K. Kavukcuoglu, G. v. d. Driessche, E. Lockhart, L. C. Cobo, F. Stimberg, et al · 2017
Cited alongside, same era.
Compact model representation for 3d reconstruction
J. K. Pontes, C. Kong, A. Eriksson, C. Fookes, S. Sridharan, and S. Lucey · 2017
Cited alongside, same era.
Image2mesh: A learning framework for single image 3d reconstruction
J. K. Pontes, C. Kong, S. Sridharan, S. Lucey, A. Eriksson, and C. Fookes · 2017
Cited alongside, same era.
P. Achlioptas, O. Diamanti, I. Mitliagkas, and L. Guibas · 2018
Closest in time.
Multiresolution tree networks for 3d point cloud processing
M. Gadelha, R. Wang, and S. Maji · 2018
Closest in time.
Learning free-form deformations for 3d object reconstruction
D. Jack, J. K. Pontes, S. Sridharan, C. Fookes, S. Shirazi, F. Maire, and A. Eriksson · 2018
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Gal: Geometric adversarial loss for single-view 3d-object reconstruction
L. Jiang, S. Shi, X. Qi, and J. Jia · 2018
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Learning category-specific mesh reconstruction from image collections
A. Kanazawa, S. Tulsiani, A. A. Efros, and J. Malik · 2018
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Splatnet: Sparse lattice networks for point cloud processing
H. Su, V. Jampani, D. Sun, S. Maji, E. Kalogerakis, M.-H. Yang, and J. Kautz · 2018
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X-vision: An augmented vision tool with real-time sensing ability in tagged environments
Y. Sun, S. N. R. Kantareddy, R. Bhattacharyya, and S. E. Sarm · 2018
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Im2avatar: Colorful 3d reconstruction from a single image
Y. Sun, Z. Liu, Y. Wang, and S. E. Sarma · 2018
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Rgcnn: Regularized graph cnn for point cloud segmentation
G. Te, W. Hu, Z. Guo, and A. Zheng · 2018
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Pixel2mesh: Generating 3d mesh models from single rgb images
N. Wang, Y. Zhang, Z. Li, Y. Fu, W. Liu, and Y.-G. Jiang · 2018
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Dynamic graph cnn for learning on point clouds
Y. Wang, Y. Sun, Z. Liu, S. E. Sarma, M. M. Bronstein, and J. M. Solomon · 2018
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Foldingnet: Point cloud auto-encoder via deep grid deformation
Y. Yang, C. Feng, Y. Shen, and D. Tian · 2018
Closest in time.
Pu-net: Point cloud upsampling network
L. Yu, X. Li, C.-W. Fu, D. Cohen-Or, and P.-A. Heng · 2018
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Pcn: Point completion network
W. Yuan, T. Khot, D. Held, C. Mertz, and M. Hebert · 2018
Closest in time.
Self-attention generative adversarial networks
H. Zhang, I. Goodfellow, D. Metaxas, and A. Odena · 2018
Closest in time.