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3D shape models are naturally parameterized using vertices and faces, \ie, composed of polygons forming a surface.
An algorithm and data structure for 3d object synthesis using surface patch intersections
W. E. Carlson · 1982
Earlier work this paper cites.
On spectral clustering: Analysis and an algorithm
A. Y. Ng, M. I. Jordan, and Y. Weiss · 2001
Earlier work this paper cites.
Geometry images
X. Gu, S. J. Gortler, and H. Hoppe · 2002
Earlier work this paper cites.
Shape distributions
R. Osada, T. Funkhouser, B. Chazelle, and D. Dobkin · 2002
Earlier work this paper cites.
Spherical parametrization and remeshing
E. Praun and H. Hoppe · 2003
Earlier work this paper cites.
Probabilistic reasoning for assembly-based 3d modeling
S. Chaudhuri, E. Kalogerakis, L. Guibas, and V. Koltun · 2011
Earlier work this paper cites.
Blended intrinsic maps
V. G. Kim, Y. Lipman, and T. Funkhouser · 2011
Earlier work this paper cites.
A probabilistic model for component-based shape synthesis
E. Kalogerakis, S. Chaudhuri, D. Koller, and V. Koltun · 2012
Earlier work this paper cites.
Consistent shape maps via semidefinite programming
Q.-X. Huang and L. Guibas · 2013
Earlier work this paper cites.
Detailed 3d representations for object recognition and modeling
M. Z. Zia, M. Stark, B. Schiele, and K. Schindler · 2013
Earlier work this paper cites.
Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada
Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger, editors · 2014
Earlier work this paper cites.
Multi-scale kernels using random walks
A. Sinha and K. Ramani · 2014
Earlier work this paper cites.
Real-time continuous pose recovery of human hands using convolutional networks
J. Tompson, M. Stein, Y. Lecun, and K. Perlin · 2014
Earlier work this paper cites.
Beyond pascal: A benchmark for 3d object detection in the wild
Y. Xiang, R. Mottaghi, and S. Savarese · 2014
Cited alongside, same era.
Learning to generate chairs with convolutional neural networks
A.Dosovitskiy, J.T.Springenberg, and T.Brox · 2015
Cited alongside, same era.
Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015
F. R. Bach and D. M. Blei, editors · 2015
Cited alongside, same era.
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, and Others · 2015
Cited alongside, same era.
Robust nonrigid registration by convex optimization
Q. Chen and V. Koltun · 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
Later among the works it cites.
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
Later among the works it cites.
Learning a Predictable and Generative Vector Representation for Objects
R. Girdhar, D. F. Fouhey, M. Rodriguez, and A. Gupta · 2016
Later among the works it cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Later among the works it cites.
Fpnn: Field probing neural networks for 3d data
Y. Li, S. Pirk, H. Su, C. R. Qi, and L. J. Guibas · 2016
Later among the works it cites.
Point registration via efficient convex relaxation
H. Maron, N. Dym, I. Kezurer, S. Kovalsky, and Y. Lipman · 2016
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C. Choi, A. Sinha, J. Hee Choi, S. Jang, and K. Ramani · 2015
Cited alongside, same era.
Analysis and synthesis of 3d shape families via deep-learned generative models of surfaces
H. Huang, E. Kalogerakis, and B. Marlin · 2015
Cited alongside, same era.
Category-specific object reconstruction from a single image
A. Kar, S. Tulsiani, J. Carreira, and J. Malik · 2015
Cited alongside, same era.
Training a feedback loop for hand pose estimation
M. Oberweger, P. Wohlhart, and V. Lepetit · 2015
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
Cited alongside, same era.
Accurate, robust, and flexible real-time hand tracking
T. Sharp, C. Keskin, D. Robertson, J. Taylor, J. Shotton, D. K. C. R. I. Leichter, A. V. Y. Wei, D. F. P. K. E. Krupka, A. Fitzgibbon, and S. Izadi · 2015
Cited alongside, same era.
Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views
H. Su, C. R. Qi, Y. Li, and L. J. Guibas · 2015
Cited alongside, same era.
Later among the works it cites.
Unsupervised learning of 3d structure from images
D. J. Rezende, S. M. A. Eslami, S. Mohamed, P. Battaglia, M. Jaderberg, and N. Heess · 2016
Later among the works it cites.
Vconv-dae: Deep volumetric shape learning without object labels
A. Sharma, O. Grau, and M. Fritz · 2016
Later among the works it cites.
Deep learning 3d shape surfaces using geometry images
A. Sinha, J. Bai, and K. Ramani · 2016
Later among the works it cites.
Deephand: Robust hand pose estimation by completing a matrix imputed with deep features
A. Sinha, C. Choi, and K. Ramani · 2016
Later among the works it cites.
Dense human body correspondences using convolutional networks
L. Wei, Q. Huang, D. Ceylan, E. Vouga, and H. Li · 2016
Later among the works it cites.
Single image 3d interpreter network
J. Wu, T. Xue, J. J. Lim, Y. Tian, J. B. Tenenbaum, A. Torralba, and W. T. Freeman · 2016
Later among the works it cites.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. B. Tenenbaum · 2016
Later among the works it cites.