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Thomas Pock
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2020 – today
- 2024
- [j51]Stefan Herdy, Emilio Rodríguez-Caballero, Thomas Pock, Bettina Weber:
Utilization of deep learning tools to map and monitor biological soil crusts. Ecol. Informatics 79: 102417 (2024) - [j50]Dominik Narnhofer
, Andreas Habring, Martin Holler
, Thomas Pock:
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging. SIAM J. Imaging Sci. 17(1): 301-333 (2024) - [j49]Muhamed Kuric, Jan Ahmetspahic, Thomas Pock:
Total Generalized Variation on a Tree. SIAM J. Imaging Sci. 17(2): 1040-1077 (2024) - [c100]Robert Harb, Thomas Pock, Heimo Müller:
Diffusion-based generation of Histopathological Whole Slide Images at a Gigapixel scale. WACV 2024: 5119-5128 - [i58]Filip Ilic, He Zhao, Thomas Pock, Richard P. Wildes:
Selective, Interpretable, and Motion Consistent Privacy Attribute Obfuscation for Action Recognition. CoRR abs/2403.12710 (2024) - [i57]Lea Bogensperger, Dominik Narnhofer, Alexander Falk, Konrad Schindler, Thomas Pock:
FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms. CoRR abs/2405.18087 (2024) - 2023
- [j48]Martin Zach
, Florian Knoll
, Thomas Pock
:
Stable Deep MRI Reconstruction Using Generative Priors. IEEE Trans. Medical Imaging 42(12): 3817-3832 (2023) - [c99]Lea Bogensperger, Dominik Narnhofer, Filip Ilic, Thomas Pock:
Score-Based Generative Models for Medical Image Segmentation Using Signed Distance Functions. DAGM 2023: 3-17 - [c98]Martin Zach
, Thomas Pock
, Erich Kobler
, Antonin Chambolle
:
Explicit Diffusion of Gaussian Mixture Model Based Image Priors. SSVM 2023: 3-15 - [c97]Lea Bogensperger, Antonin Chambolle, Alexander Effland
, Thomas Pock:
Learned Discretization Schemes for the Second-Order Total Generalized Variation. SSVM 2023: 484-497 - [c96]Lydia Lindner, Alexander Effland
, Filip Ilic, Thomas Pock, Erich Kobler:
Lightweight Video Denoising using Aggregated Shifted Window Attention. WACV 2023: 351-360 - [i56]Martin Zach
, Thomas Pock, Erich Kobler, Antonin Chambolle:
Explicit Diffusion of Gaussian Mixture Model Based Image Priors. CoRR abs/2302.08411 (2023) - [i55]Tatiana A. Bubba, Luca Calatroni, Ambra Catozzi
, Serena Crisci, Thomas Pock, Monica Pragliola, Siiri Rautio, Danilo Riccio, Andrea Sebastiani:
Bilevel learning of regularization models and their discretization for image deblurring and super-resolution. CoRR abs/2302.10056 (2023) - [i54]Erich Kobler, Thomas Pock:
Learning Gradually Non-convex Image Priors Using Score Matching. CoRR abs/2302.10502 (2023) - [i53]Lea Bogensperger, Dominik Narnhofer, Filip Ilic, Thomas Pock:
Score-Based Generative Models for Medical Image Segmentation using Signed Distance Functions. CoRR abs/2303.05966 (2023) - [i52]Lea Bogensperger, Antonin Chambolle, Alexander Effland, Thomas Pock:
Learned Discretization Schemes for the Second-Order Total Generalized Variation. CoRR abs/2303.09349 (2023) - [i51]Tim Tsz-Kit Lau, Han Liu, Thomas Pock:
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms. CoRR abs/2305.15988 (2023) - [i50]Edi Muskardin, Martin Tappler, Ingo Pill, Bernhard K. Aichernig, Thomas Pock:
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth. CoRR abs/2306.16854 (2023) - [i49]Robert Harb, Thomas Pock, Heimo Müller:
Diffusion-based generation of Histopathological Whole Slide Images at a Gigapixel scale. CoRR abs/2311.08199 (2023) - 2022
- [j47]Erich Kobler
, Alexander Effland
, Karl Kunisch
, Thomas Pock
:
Total Deep Variation: A Stable Regularization Method for Inverse Problems. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9163-9180 (2022) - [j46]Lea Bogensperger, Antonin Chambolle
, Thomas Pock:
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems. SIAM J. Math. Data Sci. 4(3): 1003-1030 (2022) - [j45]Dominik Narnhofer
, Alexander Effland
, Erich Kobler
, Kerstin Hammernik
, Florian Knoll
, Thomas Pock
:
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. IEEE Trans. Medical Imaging 41(2): 279-291 (2022) - [c95]Thomas Pinetz
, Erich Kobler, Thomas Pock, Alexander Effland
:
Blind Single Image Super-Resolution via Iterated Shared Prior Learning. GCPR 2022: 151-165 - [c94]Filip Ilic
, Thomas Pock
, Richard P. Wildes
:
Is Appearance Free Action Recognition Possible? ECCV (4) 2022: 156-173 - [c93]Markus Hofinger
, Erich Kobler
, Alexander Effland
, Thomas Pock
:
Learned Variational Video Color Propagation. ECCV (23) 2022: 512-530 - [i48]Martin Zach
, Erich Kobler, Thomas Pock:
Computed Tomography Reconstruction using Generative Energy-Based Priors. CoRR abs/2203.12658 (2022) - [i47]Filip Ilic, Thomas Pock, Richard P. Wildes:
Is Appearance Free Action Recognition Possible? CoRR abs/2207.06261 (2022) - [i46]Martin Zach
, Florian Knoll, Thomas Pock:
Stable deep MRI reconstruction using Generative Priors. CoRR abs/2210.13834 (2022) - [i45]Dominik Narnhofer, Andreas Habring, Martin Holler, Thomas Pock:
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging. CoRR abs/2212.12499 (2022) - 2021
- [j44]Patrick Knöbelreiter
, Thomas Pock:
Learned Collaborative Stereo Refinement. Int. J. Comput. Vis. 129(9): 2565-2582 (2021) - [j43]Alexander Effland
, Erich Kobler, Thomas Pock, Marko Rajkovic, Martin Rumpf
:
Image Morphing in Deep Feature Spaces: Theory and Applications. J. Math. Imaging Vis. 63(2): 309-327 (2021) - [j42]Karli Gillette
, Matthias A. F. Gsell
, Anton J. Prassl
, Elias Karabelas
, Ursula Reiter, Gert Reiter, Thomas Grandits
, Christian Payer, Darko Stern, Martin Urschler
, Jason D. Bayer
, Christoph M. Augustin
, Aurel Neic
, Thomas Pock, Edward J. Vigmond
, Gernot Plank:
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs. Medical Image Anal. 71: 102080 (2021) - [j41]Antonin Chambolle
, Thomas Pock:
Learning Consistent Discretizations of the Total Variation. SIAM J. Imaging Sci. 14(2): 778-813 (2021) - [j40]Thomas Pinetz
, Erich Kobler, Thomas Pock, Alexander Effland
:
Shared Prior Learning of Energy-Based Models for Image Reconstruction. SIAM J. Imaging Sci. 14(4): 1706-1748 (2021) - [c92]Thomas Grandits
, Simone Pezzuto
, Francisco Sahli Costabal, Paris Perdikaris, Thomas Pock
, Gernot Plank
, Rolf Krause
:
Learning Atrial Fiber Orientations and Conductivity Tensors from Intracardiac Maps Using Physics-Informed Neural Networks. FIMH 2021: 650-658 - [c91]Vladimir Kolmogorov, Thomas Pock:
One-sided Frank-Wolfe algorithms for saddle problems. ICML 2021: 5665-5675 - [i44]Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock:
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. CoRR abs/2102.06665 (2021) - [i43]Thomas Grandits, Alexander Effland, Thomas Pock, Rolf Krause, Gernot Plank, Simone Pezzuto:
GEASI: Geodesic-based Earliest Activation Sites Identification in cardiac models. CoRR abs/2102.09962 (2021) - [i42]Thomas Grandits, Simone Pezzuto, Francisco Sahli Costabal, Paris Perdikaris, Thomas Pock, Gernot Plank, Rolf Krause:
Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks. CoRR abs/2102.10863 (2021) - 2020
- [j39]Katrin Lasinger
, Christoph Vogel, Thomas Pock, Konrad Schindler:
3D Fluid Flow Estimation with Integrated Particle Reconstruction. Int. J. Comput. Vis. 128(4): 1012-1027 (2020) - [j38]Thomas Grandits
, Karli Gillette, Aurel Neic
, Jason D. Bayer
, Edward J. Vigmond, Thomas Pock, Gernot Plank
:
An inverse Eikonal method for identifying ventricular activation sequences from epicardial activation maps. J. Comput. Phys. 419: 109700 (2020) - [j37]Joan Bruna, Eldad Haber, Gitta Kutyniok
, Thomas Pock, René Vidal:
Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science. J. Math. Imaging Vis. 62(3): 277-278 (2020) - [j36]Alexander Effland
, Erich Kobler, Karl Kunisch, Thomas Pock:
Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration. J. Math. Imaging Vis. 62(3): 396-416 (2020) - [j35]Antonin Chambolle
, Martin Holler
, Thomas Pock
:
A Convex Variational Model for Learning Convolutional Image Atoms from Incomplete Data. J. Math. Imaging Vis. 62(3): 417-444 (2020) - [j34]Antonin Chambolle
, Thomas Pock:
Crouzeix-Raviart Approximation of the Total Variation on Simplicial Meshes. J. Math. Imaging Vis. 62(6-7): 872-899 (2020) - [j33]Mahesh Chandra Mukkamala
, Peter Ochs, Thomas Pock, Shoham Sabach:
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Nonconvex Optimization. SIAM J. Math. Data Sci. 2(3): 658-682 (2020) - [j32]Florian Knoll
, Kerstin Hammernik
, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya
:
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. IEEE Signal Process. Mag. 37(1): 128-140 (2020) - [c90]Christian Sormann, Patrick Knöbelreiter, Andreas Kuhn, Mattia Rossi, Thomas Pock, Friedrich Fraundorfer:
BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo. 3DV 2020: 394-403 - [c89]Erich Kobler, Alexander Effland
, Karl Kunisch, Thomas Pock:
Total Deep Variation for Linear Inverse Problems. CVPR 2020: 7546-7555 - [c88]Patrick Knöbelreiter, Christian Sormann, Alexander Shekhovtsov
, Friedrich Fraundorfer, Thomas Pock:
Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems. CVPR 2020: 7897-7906 - [c87]Christian Kopf, Thomas Pock, Bernhard Blaschitz
, Svorad Stolc:
Inline Double Layer Depth Estimation with Transparent Materials. GCPR 2020: 418-431 - [c86]Markus Hofinger
, Samuel Rota Bulò
, Lorenzo Porzi
, Arno Knapitsch
, Thomas Pock
, Peter Kontschieder
:
Improving Optical Flow on a Pyramid Level. ECCV (28) 2020: 770-786 - [c85]Thomas Grandits
, Simone Pezzuto
, Jolijn M. Lubrecht, Thomas Pock, Gernot Plank, Rolf Krause
:
PIEMAP: Personalized Inverse Eikonal Model from Cardiac Electro-Anatomical Maps. M&Ms and EMIDEC/STACOM@MICCAI 2020: 76-86 - [i41]Erich Kobler, Alexander Effland, Karl Kunisch, Thomas Pock:
Total Deep Variation for Linear Inverse Problems. CoRR abs/2001.05005 (2020) - [i40]Patrick Knöbelreiter, Christian Sormann, Alexander Shekhovtsov, Friedrich Fraundorfer, Thomas Pock:
Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems. CoRR abs/2003.06258 (2020) - [i39]Erich Kobler, Alexander Effland, Karl Kunisch, Thomas Pock:
Total Deep Variation: A Stable Regularizer for Inverse Problems. CoRR abs/2006.08789 (2020) - [i38]Christian Sormann, Patrick Knöbelreiter, Andreas Kuhn, Mattia Rossi, Thomas Pock, Friedrich Fraundorfer:
BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo. CoRR abs/2010.12436 (2020) - [i37]Thomas Pinetz, Erich Kobler, Thomas Pock, Alexander Effland:
Shared Prior Learning of Energy-Based Models for Image Reconstruction. CoRR abs/2011.06539 (2020)
2010 – 2019
- 2019
- [j31]Alexander Effland
, Erich Kobler, Anne Brandenburg, Teresa Klatzer, Leonie Neuhäuser
, Michael Hölzel, Jennifer Landsberg, Thomas Pock, Martin Rumpf
:
Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data. Int. J. Comput. Assist. Radiol. Surg. 14(4): 587-599 (2019) - [j30]Antonin Chambolle
, Thomas Pock:
Total roto-translational variation. Numerische Mathematik 142(3): 611-666 (2019) - [j29]Peter Ochs, Thomas Pock:
Adaptive FISTA for Nonconvex Optimization. SIAM J. Optim. 29(4): 2482-2503 (2019) - [c84]Patrick Knöbelreiter
, Thomas Pock
:
Learned Collaborative Stereo Refinement. GCPR 2019: 3-17 - [c83]Thomas Pinetz
, Daniel Soukup, Thomas Pock:
On the Estimation of the Wasserstein Distance in Generative Models. GCPR 2019: 156-170 - [c82]Patricia M. Johnson, Matthew J. Muckley
, Mary Bruno, Erich Kobler, Kerstin Hammernik
, Thomas Pock, Florian Knoll
:
Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions. MLMIR@MICCAI 2019: 71-79 - [c81]Senanayak Sesh Kumar Karri, Francis R. Bach, Thomas Pock:
Fast Decomposable Submodular Function Minimization using Constrained Total Variation. NeurIPS 2019: 8183-8193 - [c80]Alexander Effland
, Erich Kobler
, Thomas Pock
, Martin Rumpf
:
Time Discrete Geodesics in Deep Feature Spaces for Image Morphing. SSVM 2019: 171-182 - [i36]Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction. CoRR abs/1904.01112 (2019) - [i35]Mahesh Chandra Mukkamala, Peter Ochs, Thomas Pock, Shoham Sabach:
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization. CoRR abs/1904.03537 (2019) - [i34]Senanayak Sesh Kumar Karri, Francis R. Bach, Thomas Pock:
Fast Decomposable Submodular Function Minimization using Constrained Total Variation. CoRR abs/1905.11327 (2019) - [i33]Alexander Effland, Erich Kobler, Karl Kunisch, Thomas Pock:
An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration. CoRR abs/1907.08488 (2019) - [i32]Patrick Knöbelreiter, Christoph Vogel, Thomas Pock:
Self-Supervised Learning for Stereo Reconstruction on Aerial Images. CoRR abs/1907.12446 (2019) - [i31]Patrick Knöbelreiter, Thomas Pock:
Learned Collaborative Stereo Refinement. CoRR abs/1907.13391 (2019) - [i30]Thomas Pinetz, Daniel Soukup, Thomas Pock:
On the estimation of the Wasserstein distance in generative models. CoRR abs/1910.00888 (2019) - [i29]Alexander Effland, Erich Kobler, Thomas Pock, Marko Rajkovic, Martin Rumpf:
Image Morphing in Deep Feature Spaces: Theory and Applications. CoRR abs/1910.12672 (2019) - [i28]Markus Hofinger, Samuel Rota Bulò, Lorenzo Porzi, Arno Knapitsch, Thomas Pock, Peter Kontschieder:
The Five Elements of Flow. CoRR abs/1912.10739 (2019) - 2018
- [j28]Gottfried Munda, Christian Reinbacher
, Thomas Pock:
Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation. Int. J. Comput. Vis. 126(12): 1381-1393 (2018) - [j27]Doris Antensteiner
, Svorad Stolc, Thomas Pock:
A Review of Depth and Normal Fusion Algorithms. Sensors 18(2): 431 (2018) - [j26]Yura Malitsky
, Thomas Pock:
A First-Order Primal-Dual Algorithm with Linesearch. SIAM J. Optim. 28(1): 411-432 (2018) - [c79]Christoph Vogel
, Patrick Knöbelreiter
, Thomas Pock
:
Learning Energy Based Inpainting for Optical Flow. ACCV (6) 2018: 340-356 - [c78]Alexander Effland
, Michael Hölzel, Teresa Klatzer, Erich Kobler, Jennifer Landsberg, Leonie Neuhäuser, Thomas Pock, Martin Rumpf
:
Variational Networks for Joint Image Reconstruction and Classification of Tumor Immune Cell Interactions in Melanoma Tissue Sections. Bildverarbeitung für die Medizin 2018: 334-340 - [c77]Katrin Lasinger
, Christoph Vogel, Thomas Pock
, Konrad Schindler
:
3D Fluid Flow Estimation with Integrated Particle Reconstruction. GCPR 2018: 315-332 - [c76]Erich Kobler, Matthew J. Muckley
, Baiyu Chen, Florian Knoll
, Kerstin Hammernik
, Thomas Pock, Daniel K. Sodickson, Ricardo Otazo:
Variational Deep Learning for Low-Dose Computed Tomography. ICASSP 2018: 6687-6691 - [c75]Doris Antensteiner
, Svorad Stolc, Thomas Pock:
Variational Fusion of Light Field and Photometric Stereo for Precise 3D Sensing within a Multi-Line Scan Framework. ICPR 2018: 1036-1042 - [c74]Patrick Knöbelreiter, Christoph Vogel, Thomas Pock:
Self-Supervised Learning for Stereo Reconstruction on Aerial Images. IGARSS 2018: 4379-4382 - [i27]Markus Hofinger, Thomas Pock, Thomas Moosbrugger:
Robust Deformation Estimation in Wood-Composite Materials using Variational Optical Flow. CoRR abs/1802.04546 (2018) - [i26]Katrin Lasinger, Christoph Vogel, Thomas Pock, Konrad Schindler:
Variational 3D-PIV with Sparse Descriptors. CoRR abs/1804.02872 (2018) - [i25]Katrin Lasinger, Christoph Vogel, Thomas Pock, Konrad Schindler:
3D Fluid Flow Estimation with Integrated Particle Reconstruction. CoRR abs/1804.03037 (2018) - [i24]Christoph Vogel, Patrick Knöbelreiter, Thomas Pock:
Learning Energy Based Inpainting for Optical Flow. CoRR abs/1811.03721 (2018) - 2017
- [j25]Tuomo Valkonen
, Thomas Pock:
Acceleration of the PDHGM on Partially Strongly Convex Functions. J. Math. Imaging Vis. 59(3): 394-414 (2017) - [j24]Yunjin Chen, Thomas Pock:
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration. IEEE Trans. Pattern Anal. Mach. Intell. 39(6): 1256-1272 (2017) - [c73]Kerstin Hammernik
, Tobias Würfl, Thomas Pock, Andreas K. Maier:
A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction. Bildverarbeitung für die Medizin 2017: 92-97 - [c72]Audrey Richard, Christoph Vogel, Maros Blaha, Thomas Pock, Konrad Schindler:
Semantic 3D Reconstruction with Finite Element Bases. BMVC 2017 - [c71]Patrick Knöbelreiter, Christian Reinbacher, Alexander Shekhovtsov
, Thomas Pock:
End-to-End Training of Hybrid CNN-CRF Models for Stereo. CVPR 2017: 1456-1465 - [c70]Teresa Klatzer, Daniel Soukup, Erich Kobler, Kerstin Hammernik
, Thomas Pock:
Trainable Regularization for Multi-frame Superresolution. GCPR 2017: 90-100 - [c69]Christoph Vogel, Thomas Pock:
A Primal Dual Network for Low-Level Vision Problems. GCPR 2017: 189-202 - [c68]Erich Kobler, Teresa Klatzer, Kerstin Hammernik
, Thomas Pock:
Variational Networks: Connecting Variational Methods and Deep Learning. GCPR 2017: 281-293 - [c67]Gottfried Munda, Alexander Shekhovtsov
, Patrick Knöbelreiter, Thomas Pock:
Scalable Full Flow with Learned Binary Descriptors. GCPR 2017: 321-332 - [c66]Doris Antensteiner
, Svorad Stolc, Kristián Valentín, Bernhard Blaschitz
, Reinhold Huber-Mörk, Thomas Pock:
High-Precision 3D Sensing with Hybrid Light Field & Photometric Stereo Approach in Multi-Line Scan Framework. IRIACV 2017: 52-60 - [c65]Thomas Grandits
, Thomas Pock:
Optimizing Wavelet Bases for Sparser Representations. EMMCVPR 2017: 249-262 - [c64]Christian Reinbacher, Gottfried Munda, Thomas Pock:
Real-time panoramic tracking for event cameras. ICCP 2017: 106-114 - [c63]Stefan Heber, Wei Yu, Thomas Pock:
Neural EPI-Volume Networks for Shape from Light Field. ICCV 2017: 2271-2279 - [i23]Christian Reinbacher, Gottfried Munda, Thomas Pock:
Real-Time Panoramic Tracking for Event Cameras. CoRR abs/1703.05161 (2017) - [i22]Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, Florian Knoll:
Learning a Variational Network for Reconstruction of Accelerated MRI Data. CoRR abs/1704.00447 (2017) - [i21]Gottfried Munda, Alexander Shekhovtsov, Patrick Knöbelreiter, Thomas Pock:
Scalable Full Flow with Learned Binary Descriptors. CoRR abs/1707.06427 (2017) - [i20]Audrey Richard, Christoph Vogel, Maros Blaha, Thomas Pock, Konrad Schindler:
Semantic 3D Reconstruction with Finite Element Bases. CoRR abs/1710.01749 (2017) - 2016
- [j23]Antonin Chambolle
, Thomas Pock:
An introduction to continuous optimization for imaging. Acta Numer. 25: 161-319 (2016) - [j22]Peter Ochs, René Ranftl, Thomas Brox, Thomas Pock:
Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems. J. Math. Imaging Vis. 56(2): 175-194 (2016) - [j21]Antonin Chambolle
, Thomas Pock:
On the ergodic convergence rates of a first-order primal-dual algorithm. Math. Program. 159(1-2): 253-287 (2016) - [j20]Vladimir Kolmogorov, Thomas Pock, Michal Rolínek:
Total Variation on a Tree. SIAM J. Imaging Sci. 9(2): 605-636 (2016) - [j19]Thomas Pock, Shoham Sabach:
Inertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems. SIAM J. Imaging Sci. 9(4): 1756-1787 (2016) - [c62]Stefan Heber, Wei Yu, Thomas Pock:
U-shaped Networks for Shape from Light Field. BMVC 2016 - [c61]Christian Reinbacher, Gottfried Graber, Thomas Pock:
Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation. BMVC 2016 - [c60]Maros Blaha, Christoph Vogel, Audrey Richard, Jan Dirk Wegner, Thomas Pock, Konrad Schindler:
Large-Scale Semantic 3D Reconstruction: An Adaptive Multi-resolution Model for Multi-class Volumetric Labeling. CVPR 2016: 3176-3184 - [c59]Stefan Heber, Thomas Pock:
Convolutional Networks for Shape from Light Field. CVPR 2016: 3746-3754 - [c58]Teresa Klatzer, Kerstin Hammernik
, Patrick Knöbelreiter, Thomas Pock:
Learning joint demosaicing and denoising based on sequential energy minimization. ICCP 2016: 1-11 - [i19]Alexander Shekhovtsov, Christian Reinbacher, Gottfried Graber, Thomas Pock:
Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization. CoRR abs/1601.06274 (2016) - [i18]Christian Reinbacher, Gottfried Graber, Thomas Pock:
Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation. CoRR abs/1607.06283 (2016) - [i17]Patrick Knöbelreiter, Christian Reinbacher, Alexander Shekhovtsov, Thomas Pock:
End-to-End Training of Hybrid CNN-CRF Models for Stereo. CoRR abs/1611.10229 (2016) - [i16]Christine Guillemot, Gerlind Plonka-Hoch, Thomas Pock, Joachim Weickert:
Inpainting-Based Image Compression (Dagstuhl Seminar 16462). Dagstuhl Reports 6(11): 90-107 (2016) - 2015
- [j18]Dirk A. Lorenz
, Thomas Pock:
An Inertial Forward-Backward Algorithm for Monotone Inclusions. J. Math. Imaging Vis. 51(2): 311-325 (2015) - [j17]Arjan Kuijper
, Thomas Pock, Kristian Bredies, Horst Bischof:
Guest Editorial: Scale Space and Variational Methods. J. Math. Imaging Vis. 52(1): 1-2 (2015) - [j16]Peter Ochs, Thomas Brox, Thomas Pock:
iPiasco: Inertial Proximal Algorithm for Strongly Convex Optimization. J. Math. Imaging Vis. 53(2): 171-181 (2015) - [j15]Peter Ochs, Alexey Dosovitskiy, Thomas Brox, Thomas Pock:
On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision. SIAM J. Imaging Sci. 8(1): 331-372 (2015) - [j14]Kristian Bredies
, Thomas Pock, Benedikt Wirth:
A Convex, Lower Semicontinuous Approximation of Euler's Elastica Energy. SIAM J. Math. Anal. 47(1): 566-613 (2015) - [c57]Gernot Riegler, René Ranftl, Matthias Rüther, Thomas Pock, Horst Bischof:
Depth Restoration via Joint Training of a Global Regression Model and CNNs. BMVC 2015: 58.1-58.12 - [c56]Gottfried Graber, Jonathan Balzer, Stefano Soatto, Thomas Pock:
Efficient minimal-surface regularization of perspective depth maps in variational stereo. CVPR 2015: 511-520 - [c55]Yunjin Chen, Wei Yu, Thomas Pock:
On learning optimized reaction diffusion processes for effective image restoration. CVPR 2015: 5261-5269 - [c54]Wei Yu, Stefan Heber, Thomas Pock:
Learning Reaction-Diffusion Models for Image Inpainting. GCPR 2015: 356-367 - [c53]Peter Ochs, René Ranftl, Thomas Brox, Thomas Pock:
Bilevel Optimization with Nonsmooth Lower Level Problems. SSVM 2015: 654-665 - [i15]Vladimir Kolmogorov, Thomas Pock, Michal Rolínek:
Total variation on a tree. CoRR abs/1502.07770 (2015) - [i14]Yunjin Chen, Wei Yu, Thomas Pock:
On learning optimized reaction diffusion processes for effective image restoration. CoRR abs/1503.05768 (2015) - [i13]Yunjin Chen, Thomas Pock:
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration. CoRR abs/1508.02848 (2015) - [i12]Tuomo Valkonen, Thomas Pock:
Acceleration of the PDHGM on strongly convex subspaces. CoRR abs/1511.06566 (2015) - 2014
- [j13]Peter Ochs, Yunjin Chen, Thomas Brox, Thomas Pock:
iPiano: Inertial Proximal Algorithm for Nonconvex Optimization. SIAM J. Imaging Sci. 7(2): 1388-1419 (2014) - [j12]Yunjin Chen, WenSen Feng, René Ranftl, Hong Qiao, Thomas Pock:
A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction. IEEE Signal Process. Lett. 21(11): 1370-1374 (2014) - [j11]Yunjin Chen, René Ranftl, Thomas Pock:
Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs. IEEE Trans. Image Process. 23(3): 1060-1072 (2014) - [c52]Stefan Heber, Thomas Pock:
Scene Flow Estimation from Light Fields via the Preconditioned Primal-Dual Algorithm. GCPR 2014: 3-14 - [c51]René Ranftl, Thomas Pock:
A Deep Variational Model for Image Segmentation. GCPR 2014: 107-118 - [c50]René Ranftl, Kristian Bredies
, Thomas Pock:
Non-local Total Generalized Variation for Optical Flow Estimation. ECCV (1) 2014: 439-454 - [c49]Stefan Heber, Thomas Pock:
Shape from Light Field Meets Robust PCA. ECCV (6) 2014: 751-767 - [e3]Andrés Bruhn, Thomas Pock, Xue-Cheng Tai:
Efficient Algorithms for Global Optimization Methods in Computer Vision - International Dagstuhl Seminar, Dagstuhl Castle, Germany, November 20-25, 2011, Revised Selected Papers. Lecture Notes in Computer Science 8293, Springer 2014, ISBN 978-3-642-54773-7 [contents] - [i11]Yunjin Chen, René Ranftl, Thomas Pock:
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs. CoRR abs/1401.2804 (2014) - [i10]Yunjin Chen, Thomas Pock, Horst Bischof:
Learning ℓ1-based analysis and synthesis sparsity priors using bi-level optimization. CoRR abs/1401.4105 (2014) - [i9]Yunjin Chen, Thomas Pock, René Ranftl, Horst Bischof:
Revisiting loss-specific training of filter-based MRFs for image restoration. CoRR abs/1401.4107 (2014) - [i8]Yunjin Chen, René Ranftl, Thomas Pock:
A bi-level view of inpainting - based image compression. CoRR abs/1401.4112 (2014) - [i7]Dirk A. Lorenz, Thomas Pock:
An accelerated forward-backward algorithm for monotone inclusions. CoRR abs/1403.3522 (2014) - [i6]Peter Ochs, Yunjin Chen, Thomas Brox, Thomas Pock:
iPiano: Inertial Proximal Algorithm for Non-Convex Optimization. CoRR abs/1404.4805 (2014) - [i5]Yunjin Chen, WenSen Feng, René Ranftl, Hong Qiao, Thomas Pock:
A higher-order MRF based variational model for multiplicative noise reduction. CoRR abs/1404.5344 (2014) - [i4]Wei Yu, Thomas Pock:
A Comparison of First-order Algorithms for Machine Learning. CoRR abs/1404.6674 (2014) - 2013
- [j10]Antonin Chambolle
, Michael Hintermüller
, Thomas Pock, Christoph Schnörr, Gabriele Steidl:
Guest Editorial: Variational Models, Convex Analysis and Numerical Optimization in Mathematical Imaging. J. Math. Imaging Vis. 47(3): 165-166 (2013) - [j9]Kristian Bredies
, Thomas Pock, Benedikt Wirth:
Convex Relaxation of a Class of Vertex Penalizing Functionals. J. Math. Imaging Vis. 47(3): 278-302 (2013) - [j8]Karl Kunisch, Thomas Pock:
A Bilevel Optimization Approach for Parameter Learning in Variational Models. SIAM J. Imaging Sci. 6(2): 938-983 (2013) - [c48]Peter Ochs, Alexey Dosovitskiy, Thomas Brox, Thomas Pock:
An Iterated L1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision. CVPR 2013: 1759-1766 - [c47]Yunjin Chen, Thomas Pock, René Ranftl, Horst Bischof
:
Revisiting Loss-Specific Training of Filter-Based MRFs for Image Restoration. GCPR 2013: 271-281 - [c46]Stefan Heber, René Ranftl, Thomas Pock:
Variational Shape from Light Field. EMMCVPR 2013: 66-79 - [c45]René Ranftl, Thomas Pock, Horst Bischof
:
Minimizing TGV-Based Variational Models with Non-convex Data Terms. SSVM 2013: 282-293 - [e2]Arjan Kuijper
, Kristian Bredies, Thomas Pock, Horst Bischof
:
Scale Space and Variational Methods in Computer Vision - 4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, June 2-6, 2013. Proceedings. Lecture Notes in Computer Science 7893, Springer 2013, ISBN 978-3-642-38266-6 [contents] - [i3]Gernot Riegler, Thomas Pock, Werner Pötzi, Astrid Veronig:
Filament and Flare Detection in Hα image sequences. CoRR abs/1304.7132 (2013) - [i2]Peter Innerhofer, Thomas Pock:
A Convex Approach for Image Hallucination. CoRR abs/1304.7153 (2013) - 2012
- [j7]Antonin Chambolle
, Daniel Cremers
, Thomas Pock:
A Convex Approach to Minimal Partitions. SIAM J. Imaging Sci. 5(4): 1113-1158 (2012) - [c44]Andreas Wendel, Michael Maurer, Gottfried Graber, Thomas Pock, Horst Bischof:
Dense reconstruction on-the-fly. CVPR 2012: 1450-1457 - [c43]Markus Unger, Manuel Werlberger, Thomas Pock, Horst Bischof
:
Joint motion estimation and segmentation of complex scenes with label costs and occlusion modeling. CVPR 2012: 1878-1885 - [c42]Stefan Heber, René Ranftl, Thomas Pock:
Approximate Envelope Minimization for Curvature Regularity. ECCV Workshops (3) 2012: 283-292 - [c41]René Ranftl, Stefan Gehrig, Thomas Pock, Horst Bischof
:
Pushing the limits of stereo using variational stereo estimation. Intelligent Vehicles Symposium 2012: 401-407 - [e1]Axel Pinz, Thomas Pock, Horst Bischof
, Franz Leberl:
Pattern Recognition - Joint 34th DAGM and 36th OAGM Symposium, Graz, Austria, August 28-31, 2012. Proceedings. Lecture Notes in Computer Science 7476, Springer 2012, ISBN 978-3-642-32716-2 [contents] - 2011
- [j6]Antonin Chambolle
, Thomas Pock:
A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging. J. Math. Imaging Vis. 40(1): 120-145 (2011) - [c40]Thomas Pock, Lukas Zebedin, Horst Bischof:
TGV-Fusion. Rainbow of Computer Science 2011: 245-258 - [c39]Markus Unger, Thomas Pock, Horst Bischof:
Global Relabeling for Continuous Optimization in Binary Image Segmentation. EMMCVPR 2011: 104-117 - [c38]Manuel Werlberger, Thomas Pock, Markus Unger, Horst Bischof:
Optical Flow Guided TV-L1 Video Interpolation and Restoration. EMMCVPR 2011: 273-286 - [c37]Thomas Pock, Antonin Chambolle
:
Diagonal preconditioning for first order primal-dual algorithms in convex optimization. ICCV 2011: 1762-1769 - [c36]Gottfried Graber, Thomas Pock, Horst Bischof:
Online 3D reconstruction using convex optimization. ICCV Workshops 2011: 708-711 - [c35]Manuel Werlberger, Markus Unger, Thomas Pock, Horst Bischof
:
Efficient Minimization of the Non-local Potts Model. SSVM 2011: 314-325 - [i1]Andrés Bruhn, Thomas Pock, Xue-Cheng Tai:
Efficient Algorithms for Global Optimisation Methods in Computer Vision (Dagstuhl Seminar 11471). Dagstuhl Reports 1(11): 66-90 (2011) - 2010
- [j5]Franz Leberl, Horst Bischof
, Thomas Pock, Arnold Irschara, Stefan Kluckner:
Aerial Computer Vision for a 3D Virtual Habitat. Computer 43(6): 24-31 (2010) - [j4]Christian Bauer, Thomas Pock, Erich Sorantin, Horst Bischof, Reinhard Beichel:
Segmentation of interwoven 3d tubular tree structures utilizing shape priors and graph cuts. Medical Image Anal. 14(2): 172-184 (2010) - [j3]Kristian Bredies
, Karl Kunisch, Thomas Pock:
Total Generalized Variation. SIAM J. Imaging Sci. 3(3): 492-526 (2010) - [j2]Thomas Pock, Daniel Cremers, Horst Bischof, Antonin Chambolle
:
Global Solutions of Variational Models with Convex Regularization. SIAM J. Imaging Sci. 3(4): 1122-1145 (2010) - [c34]Jakob Santner, Thomas Pock, Horst Bischof:
Interactive Multi-label Segmentation. ACCV (1) 2010: 397-410 - [c33]Jakob Santner, Christian Leistner, Amir Saffari, Thomas Pock, Horst Bischof:
PROST: Parallel robust online simple tracking. CVPR 2010: 723-730 - [c32]Manuel Werlberger, Thomas Pock, Horst Bischof:
Motion estimation with non-local total variation regularization. CVPR 2010: 2464-2471 - [c31]Christian Reinbacher
, Thomas Pock, Christian Bauer, Horst Bischof:
Variational segmentation of elongated volumetric structures. CVPR 2010: 3177-3184 - [c30]Amir Saffari, Martin Godec, Thomas Pock, Christian Leistner, Horst Bischof:
Online multi-class LPBoost. CVPR 2010: 3570-3577 - [c29]Stefan Kluckner, Thomas Pock, Horst Bischof:
Exploiting Redundancy for Aerial Image Fusion Using Convex Optimization. DAGM-Symposium 2010: 303-312 - [c28]Markus Unger, Thomas Pock, Manuel Werlberger, Horst Bischof:
A Convex Approach for Variational Super-Resolution. DAGM-Symposium 2010: 313-322 - [c27]Kalin Kolev, Thomas Pock, Daniel Cremers
:
Anisotropic Minimal Surfaces Integrating Photoconsistency and Normal Information for Multiview Stereo. ECCV (3) 2010: 538-551 - [c26]Sasa Grbic, Martin Urschler
, Thomas Pock, Horst Bischof
:
Optical flow based deformable volume registration using a novel second-order regularization prior. Medical Imaging: Image Processing 2010: 76232R
2000 – 2009
- 2009
- [c25]Jakob Santner, Markus Unger, Thomas Pock, Christian Leistner, Amir Saffari, Horst Bischof:
Interactive Texture Segmentation using Random Forests and Total Variation. BMVC 2009: 1-12 - [c24]Manuel Werlberger, Werner Trobin, Thomas Pock, Andreas Wedel, Daniel Cremers
, Horst Bischof:
Anisotropic Huber-L1 Optical Flow. BMVC 2009: 1-11 - [c23]Thomas Pock, Antonin Chambolle
, Daniel Cremers
, Horst Bischof:
A convex relaxation approach for computing minimal partitions. CVPR 2009: 810-817 - [c22]Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Daniel Cremers
:
Video Super Resolution Using Duality Based TV-L1 Optical Flow. DAGM-Symposium 2009: 432-441 - [c21]Markus Unger, Thomas Mauthner, Thomas Pock, Horst Bischof:
Tracking as Segmentation of Spatial-Temporal Volumes by Anisotropic Weighted TV. EMMCVPR 2009: 193-206 - [c20]Thomas Pock, Daniel Cremers
, Horst Bischof, Antonin Chambolle
:
An algorithm for minimizing the Mumford-Shah functional. ICCV 2009: 1133-1140 - [c19]Frank Steinbrücker, Thomas Pock, Daniel Cremers
:
Large displacement optical flow computation withoutwarping. ICCV 2009: 1609-1614 - [c18]Andreas Wedel, Daniel Cremers
, Thomas Pock, Horst Bischof:
Structure- and motion-adaptive regularization for high accuracy optic flow. ICCV 2009: 1663-1668 - [c17]Markus Unger, Thomas Pock, Markus Grabner, Andreas Klaus, Horst Bischof:
A Variational Approach to Semiautomatic Generation of Digital Terrain Models. ISVC (2) 2009: 1119-1130 - [c16]Manuel Werlberger, Thomas Pock, Markus Unger, Horst Bischof
:
A Variational Model for Interactive Shape Prior Segmentation and Real-Time Tracking. SSVM 2009: 200-211 - [c15]Anita Sellent, Martin Eisemann, Bastian Goldlücke, Thomas Pock, Daniel Cremers, Marcus A. Magnor:
Variational Optical Flow from Alternate Exposure Images. VMV 2009: 135-144 - [c14]Frank Steinbrücker, Thomas Pock, Daniel Cremers:
Advanced Data Terms for Variational Optic Flow Estimation. VMV 2009: 155-164 - 2008
- [c13]Markus Unger, Thomas Pock, Werner Trobin, Daniel Cremers
, Horst Bischof:
TVSeg - Interactive Total Variation Based Image Segmentation. BMVC 2008: 1-10 - [c12]Thomas Pock, Markus Unger, Daniel Cremers
, Horst Bischof
:
Fast and exact solution of Total Variation models on the GPU. CVPR Workshops 2008: 1-8 - [c11]Werner Trobin, Thomas Pock, Daniel Cremers
, Horst Bischof:
An Unbiased Second-Order Prior for High-Accuracy Motion Estimation. DAGM-Symposium 2008: 396-405 - [c10]Andreas Wedel, Thomas Pock, Christopher Zach, Horst Bischof, Daniel Cremers
:
An Improved Algorithm for TV-L 1 Optical Flow. Statistical and Geometrical Approaches to Visual Motion Analysis 2008: 23-45 - [c9]Werner Trobin, Thomas Pock, Daniel Cremers
, Horst Bischof:
Continuous Energy Minimization Via Repeated Binary Fusion. ECCV (4) 2008: 677-690 - [c8]Thomas Pock, Thomas Schoenemann, Gottfried Graber, Horst Bischof, Daniel Cremers
:
A Convex Formulation of Continuous Multi-label Problems. ECCV (3) 2008: 792-805 - 2007
- [j1]Thomas Pock, Michael Pock, Horst Bischof:
Algorithmic Differentiation: Application to Variational Problems in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 29(7): 1180-1193 (2007) - [c7]Thomas Pock, Christopher Zach, Horst Bischof:
Mumford-Shah Meets Stereo: Integration of Weak Depth Hypotheses. CVPR 2007 - [c6]Christopher Zach, Thomas Pock, Horst Bischof:
A Duality Based Approach for Realtime TV-L1 Optical Flow. DAGM-Symposium 2007: 214-223 - [c5]Christopher Zach, Thomas Pock, Horst Bischof:
A Globally Optimal Algorithm for Robust TV-L1 Range Image Integration. ICCV 2007: 1-8 - [c4]Thomas Pock, Martin Urschler
, Christopher Zach, Reinhard Beichel, Horst Bischof
:
A Duality Based Algorithm for TV- L 1-Optical-Flow Image Registration. MICCAI (2) 2007: 511-518 - 2006
- [c3]Thomas Pock, Horst Bischof:
A Probabilistic Multi-phase Model for Variational Image Segmentation. DAGM-Symposium 2006: 71-80 - 2005
- [c2]Thomas Pock, Reinhard Beichel, Horst Bischof:
A Novel Robust Tube Detection Filter for 3D Centerline Extraction. SCIA 2005: 481-490 - 2004
- [c1]Reinhard Beichel, Thomas Pock, Christian Janko, Roman B. Zotter, Bernhard Reitinger, Alexander Bornik
, Kálmán Palágyi, Erich Sorantin, Georg Werkgartner, Horst Bischof, Milan Sonka
:
Liver segment approximation in CT data for surgical resection planning. Medical Imaging: Image Processing 2004
Coauthor Index
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