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In this paper, we propose a novel generative adversarial network (GAN) for 3D point clouds generation, which is called tree-GAN.
Random projection trees and low dimensional manifolds
S. Dasgupta and Y. Freund · 2008
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Convolutional-recursive deep learning for 3D object classification
R. Socher, B. Huval, B. Bath, C. D. Manning, and A. Y. Ng · 2012
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3D scene understanding by voxel-CRF
B.-S. Kim, P. Kohli, and S. Savarese · 2013
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Label propagation from imageNet to 3D point clouds
Y. Wang, R. Ji, and S.-F. Chang · 2013
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Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Object partitioning using local convexity
S. C. Stein, M. Schoeler, J. Papon, and F. Worgotter · 2014
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3D object proposals for accurate object class detection
X. Chen, K. Kundu, Y. Zhu, A. G. Berneshawi, H. Ma, S. Fidler, and R. Urtasun · 2015
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Convolutional networks on graphs for learning molecular fingerprints
D. K. Duvenaud, D. Maclaurin, J. Iparraguirre, R. Bombarell, T. Hirzel, A. Aspuru-Guzik, and R. P. Adams · 2015
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Deep convolutional networks on graph-structured data
M. Henaff, J. Bruna, and Y. LeCun · 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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Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
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Contour detection in unstructured 3d point clouds
T. Hackel, J. D. Wegner, and K. Schindler · 2016
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FPNN: Field probing neural networks for 3D data
Y. Li, S. Pirk, H. Su, C. R. Qi, and L. J. Guibas · 2016
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Gated graph sequence neural networks
Y. Li, D. Tarlow, M. Brockschmidt, and R. S. Zemel · 2016
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Blockout: Dynamic model selection for hierarchical deep networks
C. Murdock, Z. Li, H. Zhou, and T. Duerig · 2016
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Modeling and propagating CNNs in a tree structure for visual tracking
H. Nam, M. Baek, and B. Han · 2016
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Generative adversarial text to image synthesis
S. Reed, Z. Akata, L. X. Yan, B. Logeswaran, Schiele, and H. Lee · 2016
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Improved techniques for training GANs
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, X. Chen, and X. Chen · 2016
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Deep sliding shapes for a modal 3D object detection in RGB-D images
S. Song and J. Xiao · 2016
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Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna · 2016
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Generative image modeling using style and structure adversarial networks
X. Wang and A. Gupta · 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
A-Fast-RCNN: Hard positive generation via adversary for object detection
X. Wang, A. Shrivastava, and A. Gupta · 2017
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Learning representations and generative models for 3D point clouds
P. Achlioptas, O. Diamanti, I. Mitliagkas, and L. Guibas · 2018
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TreeNet: Learning sentence representations with unconstrained tree structure
Z. Cheng, C. Yuan, J. Li, and H. Yang · 2018
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SeGAN: Segmenting and generating the invisible
K. Ehsani, R. Mottaghi, and A. Farhadi · 2018
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Multiresolution tree networks for 3d point cloud processing
M. Gadelha, R. Wang, and S. Maji · 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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Cited alongside, same era.
M. Arjovsky, S. Chintala, and L. Bottou · 2017
Cited alongside, same era.
ScanNet: Richly-annotated 3D reconstructions of indoor scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Nießner · 2017
Cited alongside, same era.
A point set generation network for 3D object reconstruction from a single image
H. Fan, H. Su, and L. Guibas · 2017
Cited alongside, same era.
Improved training of wasserstein GANs
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
Cited alongside, same era.
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.
Image-to-image translation with conditional adversarial nets
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2017
Cited alongside, same era.
Later among the works it cites.
Conditional image-to-image translation
J. Lin, Y. Xia, T. Qin, Z. Chen, and T.-Y. Liu · 2018
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Tree-CNN: A deep convolutional neural network for lifelong learning
D. Roy, P. Panda, and K. Roy · 2018
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VITAL: Visual tracking via adversarial learning
Y. Song, C. Ma, X. Wu, L. Gong, L. Bao, W. Zuo, C. Shen, R. Lau, and M.-H. Yang · 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
Later among the works it cites.
FoldingNet: Point cloud auto-encoder via deep grid deformation
Y. Yang, C. Feng, Y. Shen, and D. Tian · 2018
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Generative image inpainting with contextual attention
J. Yu, Z. Lin, J. Yang, X. Shen, X. Lu, and T. S. Huang · 2018
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Translating and segmenting multimodal medical volumes with cycle- and shape-consistency generative adversarial network
Z. Zhang, L. Yang, and Y. Zheng · 2018
Later among the works it cites.
VoxelNet: End-to-end learning for point cloud based 3D object detection
Y. Zhou and O. Tuzel · 2018
Later among the works it cites.
Learning localized generative models for 3D point clouds via graph convolution
D. Valsesia, G. Fracastoro, and E. Magli · 2019
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