Fetching the paper…
Reading the bibliography…
Template 3D shapes are useful for many tasks in graphics and vision, including fitting observation data, analyzing shape collections, and transferring shape attributes.
Machine Perception of Three-Dimensional Solids
L. Roberts · 1963
Earlier work this paper cites.
A constructive geometry for computer graphics
A. Ricci · 1973
Earlier work this paper cites.
A generalization of algebraic surface drawing
J. F. Blinn · 1982
Earlier work this paper cites.
Data structure for soft objects
G. Wyvill, C. McPheeters, and B. Wyvill · 1986
Earlier work this paper cites.
Recognition-by-components: a theory of human image understanding
I. Biederman · 1987
Earlier work this paper cites.
Marching cubes: A high resolution 3d surface construction algorithm
W. E. Lorensen and H. E. Cline · 1987
Earlier work this paper cites.
Convolution surfaces
J. Bloomenthal and K. Shoemake · 1991
Earlier work this paper cites.
Volumetric shape description of range data using “blobby model”
S. Muraki · 1991
Earlier work this paper cites.
Multi-level partition of unity implicits
Y. Ohtake, A. Belyaev, M. Alexa, G. Turk, and H.-P. Seidel · 2003
Earlier work this paper cites.
Visualizing data using t-SNE
L. van der Maaten and G. Hinton · 2008
Earlier work this paper cites.
Template matching techniques in computer vision: theory and practice
R. Brunelli · 2009
Earlier work this paper cites.
Consistent segmentation of 3d models
A. Golovinskiy and T. Funkhouser · 2009
Earlier work this paper cites.
Learning 3d mesh segmentation and labeling
E. Kalogerakis, A. Hertzmann, and K. Singh · 2010
Earlier work this paper cites.
Globfit: Consistently fitting primitives by discovering global relations
Y. Li, X. Wu, Y. Chrysathou, A. Sharf, D. Cohen-Or, and N. J. Mitra · 2011
Earlier work this paper cites.
Exploration of continuous variability in collections of 3d shapes
M. Ovsjanikov, W. Li, L. Guibas, and N. J. Mitra · 2011
Earlier work this paper cites.
Co-abstraction of shape collections
M. E. Yumer and L. B. Kara · 2012
Earlier work this paper cites.
Learning part-based templates from large collections of 3d shapes
V. G. Kim, W. Li, N. J. Mitra, S. Chaudhuri, S. DiVerdi, and T. Funkhouser · 2013
Earlier work this paper cites.
Vdb: High-resolution sparse volumes with dynamic topology
K. Museth · 2013
Earlier work this paper cites.
Meta-representation of shape families
N. Fish, M. Averkiou, O. Van Kaick, O. Sorkine-Hornung, D. Cohen-Or, and N. J. Mitra · 2014
Earlier work this paper cites.
Structure-aware shape processing
N. J. Mitra, M. Wand, H. Zhang, D. Cohen-Or, V. Kim, and Q.-X. Huang · 2014
Earlier work this paper cites.
Recurring part arrangements in shape collections
Y. Zheng, D. Cohen-Or, M. Averkiou, and N. J. Mitra · 2014
Earlier work this paper cites.
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
Cited alongside, same era.
Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Cited alongside, same era.
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
Cited alongside, same era.
Voxnet: A 3d convolutional neural network for real-time object recognition
D. Maturana and S. Scherer · 2015
Cited alongside, same era.
U-net: Convolutional networks for biomedical image segmentation
Semantic correspondence across 3d models for example-based modeling
V. Léon, V. Itier, N. Bonneel, G. Lavoué, and J.-P. Vandeborre · 2017
Later among the works it cites.
Grass: Generative recursive autoencoders for shape structures
J. Li, K. Xu, S. Chaudhuri, E. Yumer, H. Zhang, and L. Guibas · 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.
Learning shape abstractions by assembling volumetric primitives
S. Tulsiani, H. Su, L. J. Guibas, A. A. Efros, and J. Malik · 2017
Later among the works it cites.
Data-driven shape analysis and processing
K. Xu, V. G. Kim, Q. Huang, and E. Kalogerakis · 2017
Later among the works it cites.
3d-prnn: Generating shape primitives with recurrent neural networks
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
Cited alongside, same era.
Multi-view convolutional neural networks for 3d shape recognition
H. Su, S. Maji, E. Kalogerakis, and E. G. 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.
Efficient single-view 3d co-segmentation using shape similarity and spatial part relations
N. Araslanov, S. Koo, J. Gall, and S. Behnke · 2016
Cited alongside, same era.
Keep it SMPL: Automatic estimation of 3D human pose and shape from a single image
F. Bogo, A. Kanazawa, C. Lassner, P. Gehler, J. Romero, and M. J. Black · 2016
Cited alongside, same era.
Generative and discriminative voxel modeling with convolutional neural networks
A. Brock, T. Lim, J. M. Ritchie, and N. Weston · 2016
Cited alongside, same era.
C. Zou, E. Yumer, J. Yang, D. Ceylan, and D. Hoiem · 2017
Later among the works it cites.
Learning implicit fields for generative shape modeling
Z. Chen and H. Zhang · 2018
Later among the works it cites.
Parsing geometry using structure-aware shape templates
V. Ganapathi-Subramanian, O. Diamanti, S. Pirk, C. Tang, M. Nießner, and L. Guibas · 2018
Later among the works it cites.
A papier-mâché approach to learning 3d surface generation
T. Groueix, M. Fisher, V. G. Kim, B. C. Russell, and M. Aubry · 2018
Later among the works it cites.
Functionality representations and applications for shape analysis
R. Hu, M. Savva, and O. van Kaick · 2018
Later among the works it cites.
A survey of simple geometric primitives detection methods for captured 3d data
A. Kaiser, J. A. Ybanez Zepeda, and T. Boubekeur · 2018
Later among the works it cites.
Learning category-specific mesh reconstruction from image collections
A. Kanazawa, S. Tulsiani, A. A. Efros, and J. Malik · 2018
Later among the works it cites.
Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
A. Kanezaki, Y. Matsushita, and Y. Nishida · 2018
Later among the works it cites.
3D Shape Analysis: Fundamentals, Theory, and Applications
H. Laga, Y. Guo, H. Tabia, R. B. Fisher, and M. Bennamoun · 2018
Later among the works it cites.
Supervised fitting of geometric primitives to 3d point clouds
L. Li, M. Sung, A. Dubrovina, L. Yi, and L. Guibas · 2018
Later among the works it cites.
Occupancy networks: Learning 3d reconstruction in function space
L. M. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, and A. Geiger · 2018
Later among the works it cites.
Csgnet: Neural shape parser for constructive solid geometry
G. Sharma, R. Goyal, D. Liu, E. Kalogerakis, and S. Maji · 2018
Later among the works it cites.
Deepvoxels: Learning persistent 3d feature embeddings
V. Sitzmann, J. Thies, F. Heide, M. Nießner, G. Wetzstein, and M. Zollhöfer · 2018
Later among the works it cites.
Pixel2mesh: Generating 3d mesh models from single rgb images
N. Wang, Y. Zhang, Z. Li, Y. Fu, W. Liu, and Y.-G. Jiang · 2018
Later among the works it cites.
DeepSDF: Learning continuous signed distance functions for shape representation
J. J. Park, P. Florence, J. Straub, R. A. Newcombe, and S. Lovegrove · 2019
Closest in time.