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Geometry images
X. Gu, S. Gortler, and H. Hoppe · 2002
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Spacetime faces: High-resolution capture for modeling and animation
L. Zhang, N. Snavely, B. Curless, and S. M. Seitz · 2004
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SCAPE: shape completion and animation of people
D. Anguelov, P. Srinivasan, D. Koller, S. Thrun, J. Rodgers, and J. Davis · 2005
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Articulated mesh animation from multi-view silhouettes
D. Vlasic, I. Baran, W. Matusik, and J. Popović · 2008
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As-rigid-as-possible surface morphing
Y.-S. Liu, H.-B. Yan, and R. R. Martin · 2011
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Example-based 3D object reconstruction from line drawings
T. Xue, J. Liu, and X. Tang · 2012
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Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2013
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Rectifier nonlinearities improve neural network acoustic models
A. L. Maas, A. Y. Hannun, and A. Y. Ng · 2013
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Map-based exploration of intrinsic shape differences and variability
R. M. Rustamov, M. Ovsjanikov, O. Azencot, M. Ben-Chen, F. Chazal, and L. Guibas · 2013
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FAUST: Dataset and evaluation for 3D mesh registration
F. Bogo, J. Romero, M. Loper, and M. J. Black · 2014
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Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks
D. Boscaini, J. Masci, S. Melzi, M. M. Bronstein, U. Castellani, and P. Vandergheynst · 2015
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DRAW: A recurrent neural network for image generation
K. Gregor, I. Danihelka, A. Graves, D. Rezende, and D. Wierstra · 2015
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Analysis and synthesis of 3D shape families via deep-learned generative models of surfaces
H. Huang, E. Kalogerakis, and B. Marlin · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Mechanics Lecture Notes Part III
P. Kelly · 2015
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ADAM: A method for stochastic optimization
D. Kingma and J. Ba · 2015
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Smooth rotation enhanced as-rigid-as-possible mesh animation
Z. Levi and C. Gotsman · 2015
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Joint embeddings of shapes and images via CNN image purification
Y. Li, H. Su, C. R. Qi, N. Fish, D. Cohen-Or, and L. J. Guibas · 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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ShapeNet: Convolutional neural networks on non-Euclidean 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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Dyna: A model of dynamic human shape in motion
G. Pons-Moll, J. Romero, N. Mahmood, and M. J. Black · 2015
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Deeppano: Deep panoramic representation for 3-d shape recognition
Unsupervised learning of 3D structure from images
D. J. Rezende, S. A. Eslami, S. Mohamed, P. Battaglia, M. Jaderberg, and N. Heess · 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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Deep learning 3D shape surfaces using geometry images
A. Sinha, J. Bai, and K. Ramani · 2016
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Learning shape abstractions by assembling volumetric primitives
S. Tulsiani, H. Su, L. J. Guibas, A. A. Efros, and J. Malik · 2016
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How to use t-SNE effectively
M. Wattenberg, F. Viégas, and I. Johnson · 2016
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Single image 3D interpreter network
J. Wu, T. Xue, J. J. Lim, Y. Tian, J. B. Tenenbaum, A. Torralba, and W. T. Freeman · 2016
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B. Shi, S. Bai, Z. Zhou, and X. Bai · 2015
Cited alongside, same era.
Learning structured output representation using deep conditional generative models
K. Sohn, H. Lee, and X. Yan · 2015
Cited alongside, same era.
Multi-view convolutional neural networks for 3d shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. Learned-Miller · 2015
Cited alongside, same era.
3D ShapeNets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Cited alongside, same era.
Learning shape correspondence with anisotropic convolutional neural networks
D. Boscaini, J. Masci, E. Rodolà, and M. Bronstein · 2016
Cited alongside, same era.
Anisotropic diffusion descriptors
D. Boscaini, J. Masci, E. Rodolà, M. M. Bronstein, and D. Cremers · 2016
Cited alongside, same era.
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
Cited alongside, same era.
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Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision
X. Yan, J. Yang, E. Yumer, Y. Guo, and H. Lee · 2016
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Functional characterization of intrinsic and extrinsic geometry
E. Corman, J. Solomon, M. Ben-Chen, L. Guibas, and M. Ovsjanikov · 2017
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Smooth interpolation of key frames in a riemannian shell space
P. Huber, R. Perl, and M. Rumpf · 2017
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Image-to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2017
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GRASS: Generative recursive autoencoders for shape structures
J. Li, K. Xu, S. Chaudhuri, E. Yumer, H. Zhang, and L. Guibas · 2017
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Convolutional neural networks on surfaces via seamless toric covers
H. Maron, M. Galun, N. Aigerman, M. Trope, N. Dym, E. Yumer, V. G. Kim, and Y. Lipman · 2017
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The shape variational autoencoder: A deep generative model of part-segmented 3D objects
C. Nash and C. K. Williams · 2017
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SurfNet: Generating 3D shape surfaces using deep residual networks
A. Sinha, A. Unmesh, Q. Huang, and K. Ramani · 2017
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Mesh-based autoencoders for localized deformation component analysis
Q. Tan, L. Gao, Y.-K. Lai, J. Yang, and S. Xia · 2017
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Dynamic filters in graph convolutional networks
N. Verma, E. Boyer, and J. Verbeek · 2017
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