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We introduce the first completely unsupervised correspondence learning approach for deformable 3D shapes.
Surface simplification using quadric error metrics
M. Garland and P. S. Heckbert · 1997
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Computing geodesic paths on manifolds
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Using spin images for efficient object recognition in cluttered 3d scenes
A. E. Johnson and M. Hebert · 1999
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On bending invariant signatures for surfaces
A. Elad and R. Kimmel · 2003
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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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Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
R. R. Coifman, S. Lafon, A. B. Lee, M. Maggioni, B. Nadler, F. Warner, and S. W. Zucker · 2005
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Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching
A. M. Bronstein, M. M. Bronstein, and R. Kimmel · 2006
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Laplace-beltrami eigenfunctions for deformation invariant shape representation
R. M. Rustamov · 2007
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Numerical geometry of non-rigid shapes
A. M. Bronstein, M. M. Bronstein, and R. Kimmel · 2008
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Integral invariants for robust geometry processing
H. Pottmann, J. Wallner, Q.-X. Huang, and Y.-L. Yang · 2009
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A Concise and Provably Informative Multi-Scale Signature Based on Heat Diffusion
J. Sun, M. Ovsjanikov, and L. Guibas · 2009
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Unique signatures of histograms for local surface description
F. Tombari, S. Salti, and L. Di Stefano · 2010
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The wave kernel signature: A quantum mechanical approach to shape analysis
M. Aubry, U. Schlickewei, and D. Cremers · 2011
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Blended intrinsic maps
V. G. Kim, Y. Lipman, and T. A. Funkhouser · 2011
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Intrinsic shape matching by planned landmark sampling
A. Tevs, A. Berner, M. Wand, I. Ihrke, and H.-P. Seidel · 2011
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Discrete minimum distortion correspondence problems for non-rigid shape matching
C. Wang, M. M. Bronstein, A. M. Bronstein, and N. Paragios · 2011
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Functional maps: a flexible representation of maps between shapes
M. Ovsjanikov, M. Ben-Chen, J. Solomon, A. Butscher, and L. Guibas · 2012
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A game-theoretic approach to deformable shape matching
E. Rodolà, A. M. Bronstein, A. Albarelli, F. Bergamasco, and A. Torsello · 2012
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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 spectral descriptors for deformable shape correspondence
R. Litman and A. M. Bronstein · 2014
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Learning spectral descriptors for deformable shape correspondence
R. Litman and A. M. Bronstein · 2014
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Dense non-rigid shape correspondence using random forests
E. Rodolà, S. Rota Bulo, T. Windheuser, M. Vestner, and D. Cremers · 2014
Anisotropic diffusion descriptors
D. Boscaini, J. Masci, E. Rodolà, M. M. Bronstein, and D. Cremers · 2016
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SHREC’16: Partial matching of deformable shapes
L. Cosmo, E. Rodolà, M. M. Bronstein, et al · 2016
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Matching deformable objects in clutter
L. Cosmo, E. Rodolà, J. Masci, A. Torsello, and M. M. Bronstein · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Non-rigid puzzles
O. Litany, E. Rodolà, A. M. Bronstein, M. M. Bronstein, and D. Cremers · 2016
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Dynamic FAUST: Registering human bodies in motion
F. Bogo, J. Romero, G. Pons-Moll, and M. J. Black · 2017
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Shot: Unique signatures of histograms for surface and texture description
S. Salti, F. Tombari, and L. Di Stefano · 2014
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Hitting and commute times in large random neighborhood graphs
U. Von Luxburg, A. Radl, and M. Hein · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng · 2015
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On the optimality of shape and data representation in the spectral domain
Y. Aflalo, H. Brezis, and R. Kimmel · 2015
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On convex relaxation of graph isomorphism
Y. Aflalo, A. Bronstein, and R. Kimmel · 2015
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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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Deep functional maps: Structured prediction for dense shape correspondence
O. Litany, T. Remez, E. Rodolà, A. M. Bronstein, and M. M. Bronstein · 2017
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Fully spectral partial shape matching
O. Litany, E. Rodolà, A. M. Bronstein, and M. M. Bronstein · 2017
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Geometric deep learning on graphs and manifolds using mixture model cnns
F. Monti, D. Boscaini, J. Masci, E. Rodolà, J. Svoboda, and M. M. Bronstein · 2017
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Partial functional correspondence
E. Rodolà, L. Cosmo, M. M. Bronstein, A. Torsello, and D. Cremers · 2017
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Geodesic distance descriptors
G. Shamai and R. Kimmel · 2017
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Efficient deformable shape correspondence via kernel matching
M. Vestner, Z. Lähner, A. Boyarski, O. Litany, R. Slossberg, T. Remez, E. Rodolà, A. Bronstein, M. Bronstein, R. Kimmel, and D. Cremers · 2017
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Product manifold filter: Non-rigid shape correspondence via kernel density estimation in the product space
M. Vestner, R. Litman, E. Rodolà, A. M. Bronstein, and D. Cremers · 2017
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3d-coded : 3d correspondences by deep deformation
T. Groueix, M. Fisher, V. G. Kim, B. Russell, and M. Aubry · 2018
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Robust watertight manifold surface generation method for shapenet models
J. Huang, H. Su, and L. Guibas · 2018
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