Thomas Pock
Thomas Pock
Professor of Computer Science, TU Graz
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
A first-order primal-dual algorithm for convex problems with applications to imaging
A Chambolle, T Pock
Journal of mathematical imaging and vision 40 (1), 120-145, 2011
A Duality Based Approach for Realtime TV-L1 Optical Flow
C Zach, T Pock, H Bischof
Joint pattern recognition symposium, 214-223, 2007
Total generalized variation
K Bredies, K Kunisch, T Pock
SIAM Journal on Imaging Sciences 3 (3), 492-526, 2010
Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration
Y Chen, T Pock
IEEE transactions on pattern analysis and machine intelligence 39 (6), 1256-1272, 2016
Anisotropic Huber-L1 Optical Flow.
M Werlberger, W Trobin, T Pock, A Wedel, D Cremers, H Bischof
BMVC 1 (2), 3, 2009
Learning a variational network for reconstruction of accelerated MRI data
K Hammernik, T Klatzer, E Kobler, MP Recht, DK Sodickson, T Pock, ...
Magnetic resonance in medicine 79 (6), 3055-3071, 2018
An Improved Algorithm for TV-L1 Optical Flow
A Wedel, T Pock, C Zach, H Bischof, D Cremers
Statistical and geometrical approaches to visual motion analysis, 23-45, 2009
PROST: Parallel robust online simple tracking
J Santner, C Leistner, A Saffari, T Pock, H Bischof
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
Second order total generalized variation (TGV) for MRI
F Knoll, K Bredies, T Pock, R Stollberger
Magnetic resonance in medicine 65 (2), 480-491, 2011
Diagonal preconditioning for first order primal-dual algorithms in convex optimization
T Pock, A Chambolle
2011 International Conference on Computer Vision, 1762-1769, 2011
An algorithm for minimizing the Mumford-Shah functional
T Pock, D Cremers, H Bischof, A Chambolle
2009 IEEE 12th International Conference on Computer Vision, 1133-1140, 2009
An introduction to total variation for image analysis
A Chambolle, V Caselles, D Cremers, M Novaga, T Pock
Theoretical foundations and numerical methods for sparse recovery 9 (263-340 …, 2010
Markov random fields for vision and image processing
A Blake, P Kohli, C Rother
Mit Press, 2011
iPiano: Inertial proximal algorithm for nonconvex optimization
P Ochs, Y Chen, T Brox, T Pock
SIAM Journal on Imaging Sciences 7 (2), 1388-1419, 2014
A convex relaxation approach for computing minimal partitions
T Pock, A Chambolle, D Cremers, H Bischof
2009 IEEE Conference on Computer Vision and Pattern Recognition, 810-817, 2009
A Globally Optimal Algorithm for Robust TV-L1 Range Image Integration
C Zach, T Pock, H Bischof
2007 IEEE 11th International Conference on Computer Vision, 1-8, 2007
Motion estimation with non-local total variation regularization
M Werlberger, T Pock, H Bischof
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
Point clouds
F Leberl, A Irschara, T Pock, P Meixner, M Gruber, S Scholz, A Wiechert
Photogrammetric Engineering & Remote Sensing 76 (10), 1123-1134, 2010
A convex approach to minimal partitions
A Chambolle, D Cremers, T Pock
SIAM Journal on Imaging Sciences 5 (4), 1113-1158, 2012
A convex formulation of continuous multi-label problems
T Pock, T Schoenemann, G Graber, H Bischof, D Cremers
European conference on computer vision, 792-805, 2008
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Artikkelit 1–20