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We introduce Scan2Mesh, a novel data-driven generative approach which transforms an unstructured and potentially incomplete range scan into a structured 3D mesh representation.
The hungarian method for the assignment problem
H. W. Kuhn · 1955
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Marching cubes: A high resolution 3d surface construction algorithm
W. E. Lorensen and H. E. Cline · 1987
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A volumetric method for building complex models from range images
B. Curless and M. Levoy · 1996
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Poisson surface reconstruction
M. Kazhdan, M. Bolitho, and H. Hoppe · 2006
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The graph neural network model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2009
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Screened poisson surface reconstruction
M. Kazhdan and H. Hoppe · 2013
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2013
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 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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Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
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Completing 3d object shape from one depth image
J. Rock, T. Gupta, J. Thorsen, J. Gwak, D. Shin, and D. Hoiem · 2015
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Deep sliding shapes for amodal 3d object detection in rgb-d images
S. Song and J. Xiao · 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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Volumetric and multi-view cnns for object classification on 3d data
C. R. Qi, H. Su, M. Nießner, A. Dai, M. Yan, and L. Guibas · 2016
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3dmatch: Learning the matching of local 3d geometry in range scans
A. Zeng, S. Song, M. Nießner, M. Fisher, and J. Xiao · 2016
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
A. Dai, A. X. Chang, M. Savva, M. Halber, T. Funkhouser, and M. Nießner · 2017
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Shape completion using 3d-encoder-predictor cnns and shape synthesis
A. Dai, C. R. Qi, and M. Nießner · 2017
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A point set generation network for 3d object reconstruction from a single image
Octnet: Learning deep 3d representations at high resolutions
G. Riegler, A. O. Ulusoy, and A. Geiger · 2017
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Semantic scene completion from a single depth image
S. Song, F. Yu, A. Zeng, A. X. Chang, M. Savva, and T. Funkhouser · 2017
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Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
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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
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Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans
A. Dai, D. Ritchie, M. Bokeloh, S. Reed, J. Sturm, and M. Nießner · 2018
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Neural message passing for quantum chemistry
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High Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference
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Hierarchical surface prediction for 3d object reconstruction
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Octnetfusion: Learning depth fusion from data
G. Riegler, A. O. Ulusoy, H. Bischof, and A. Geiger · 2017
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Learning category-specific mesh reconstruction from image collections
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Neural relational inference for interacting systems
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Deep marching cubes: Learning explicit surface representations
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An intriguing failing of convolutional neural networks and the coordconv solution
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Pixel2mesh: Generating 3d mesh models from single rgb images
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Adaptive o-cnn: a patch-based deep representation of 3d shapes
P.-S. Wang, C.-Y. Sun, Y. Liu, and X. Tong · 2018
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