Thomas Pock
Short CV
Thomas Pock received his MSc (1998-2004) and his PhD (2005-2008) in Computer Engineering (Telematik) from Graz University of Technology. After a Post-doc position at the University of Bonn, he moved back to Graz University of Technology where he has been an Assistant Professor at the Institute of Computer Graphics and Vision. In 2013 Thomas Pock received the START price of the Austrian Science Fund (FWF) and the German Pattern recognition award of the German association for pattern recognition (DAGM). In 2014, he received a starting grant from the European Research Council (ERC). Since 2014 Thomas Pock is a Professor of Computer Science at Graz University of Technology, where he is leading the vision, learning and optimization (VLO) group. In 2019, he became a member (reporter) of the board of the Austrian Science Fund (FWF) for the section computer science. The focus of his research is image processing, computer vision, inverse problems, convex and non-smooth optimization, and machine learning.
Publications
Image Morphing in Deep Feature Spaces: Theory and Applications
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Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems
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Total Deep Variation for Linear Inverse Problems
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Shared Prior Learning of Energy-Based Models for Image Reconstruction
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Total Deep Variation: A Stable Regularizer for Inverse Problems
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Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration
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Improving Optical Flow on a Pyramid Level
Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings
770-786
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BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo
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Total Deep Variation for SparseCT Reconstruction
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Learning Consistent Discretizations of the Total Variation
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Approximating the Total Variation with Finite Differences or Finite ElementsHandbook of Numerical Analysis: Geometric Partial Differential Equations II
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PIEMAP: Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps
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A convex variational model for learning convolutional image atoms from incomplete data
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Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science
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Convex-Concave backtracking for inertial Bregman proximal gradient algorithms in nonconvex optimization
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Time Discrete Geodesics in Deep Feature Spaces for Image Morphing
Scale Space and Variational Methods in Computer Vision
171-182
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Combining Variational Optimization and Deep Learning for efficient ASL image quality enhancement
Magnetic Resonance Materials in Physics, Biology and Medicine
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Adaptive FISTA for nonconvex optimization
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3D Fluid Flow Estimation with Integrated Particle Reconstruction
Pattern Recognition - 40th German Conference, GCPR 2018, Proceedings
315-332
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Inverse GANs for accelerated MRI reconstruction
Wavelets and Sparsity XVIII
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Learned Collaborative Stereo Refinement
German Conference on Pattern Recognition
3-17
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On the estimation of the Wasserstein distance in generative models
German Conference on Pattern Recognition
156-170
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Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions
Machine Learning for Medical Image Reconstruction
71-79
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Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction
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Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization
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Fast Decomposable Submodular Function Minimization using Constrained Total Variation
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Image Morphing in Deep Feature Spaces: Theory and Applications
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Determination of the moisture change behavior of cross-laminated timber using an optical flow based computer vision technique
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Joint Reconstruction and Classification of Tumor Cells and Cell Interactions in Melanoma Tissue Sections with Synthesized Training Data
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Total roto-translational variation
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Robust Deformation Estimation in Wood-Composite Materials using Variational Optical Flow
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Learning Energy Based Inpainting for Optical Flow
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Self-Supervised Learning for Stereo Reconstruction on Aerial Images
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A First-Order Primal-Dual Algorithm with Linesearch
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A Review of Depth and Normal Fusion Algorithms
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Variational Networks for Joint Image Reconstruction and Classification of Tumor Immune Cell Interactions in Melanoma Tissue Sections
Bildverarbeitung für die Medizin 2018
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Variational Fusion of Light Field and Photometric Stereo for Precise 3D Sensing within a Multi-Line Scan Framework
Proceedings of the International Conference on Pattern Recognition (ICPR)
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Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation
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Assessment of the generalization of learned image reconstruction and the potential for transfer learning
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Variational Adversarial Networks for Accelerated MR Image Reconstruction
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Analysis of the influence of deviations between training and test data in learned image reconstruction
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Variational 3D-PIV with sparse descriptors
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Variational Deep Learning for Low-Dose Computed Tomography
2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
6687-6691
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Assessment of the generalization of learned image reconstruction and the potential for transfer learning
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Optimizing Wavelet Bases for Sparser Representations
Energy Minimization Methods in Computer Vision and Pattern Recognition
249-262
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Variational Networks: Connecting Variational Methods and Deep Learning
Pattern Recognition
281-293
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Improved Accelerated Model-based Parameter Quantification with Total-Generalized- Variation Regularization.
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End-to-End Training of Hybrid CNN-CRF Models for Semantic Segmentation using Structured Learning
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A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction
Bildverarbeitung für die Medizin 2017
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Variational Photoacoustic Image Reconstruction with Spatially Resolved Projection Data
Proc. SPIE
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Learning a Variational Network for Reconstruction of Accelerated MRI Data
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On the Influence of Sampling Pattern Design on Deep Learning-Based MRI Reconstruction
Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM)
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L2 or not L2: Impact of Loss Function Design for Deep Learning MRI Reconstruction
Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM)
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Accelerated Knee Imaging Using a Deep Learning Based Reconstruction
Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM)
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Trainable Nonlinear Reaction Diffusion
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Real-time panoramic tracking for event cameras
2017 IEEE International Conference on Computational Photography, ICCP 2017 - Proceedings
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Acceleration of the PDHGM on Partially Strongly Convex Functions
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Neural EPI-Volume Networks for Shape from Light Field
IEEE International Conference on Computer Vision (ICCV)
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A Primal Dual Network for Low-Level Vision Problems
German Conference on Pattern Recognition, 2017
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Eye Movements during silent and oral reading in a regular orthography
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Semantic 3D Reconstruction with Finite Element Bases
28th British Machine Vision Conference
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Trainable Regularization for Multi-frame Superresolution
Pattern Recognition
90-100
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Automated segmentation and morphometry of muscle fibers from haematoxylin-eosin-stained histological sections
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Scalable Full Flow with Learned Binary Descriptors
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Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation
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End-to-End Training of Hybrid CNN-CRF Models for Stereo
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U-shaped Networks for Shape from Light Field
British Machine Vision Conference, BMVC 2016
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On the ergodic convergence rates of a first-order primaldual algorithm
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Total variation on a tree
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Inertial proximal alternating linearized minimization (iPALM) for nonconvex and nonsmooth problems
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Learning a Variational Model for Compressed Sensing MRI Reconstruction
Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM)
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Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization
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Learning Joint Demosaicing and Denoising Based on Sequential Energy Minimization
IEEE International Conference on Computational Photography (ICCP)
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Large-Scale Semantic 3D Reconstruction: an Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling
Computer Vision and Pattern Recognition
3176-3184
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Convolutional Networks for Shape from Light Field
IEEE Conference on Computer Vision and Pattern Recognition (2016)
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Continuous Hyper-parameter Learning for Support Vector Machines
Computer Vision Winter Workshop
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Real-time flare detection in ground-based hα imaging at kanzelhhe observatory
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Vertebrae Segmentation in 3D CT Images based on a Variational FrameworkRecent Advances in Computational Methods and Clinical Applications for Spine Imaging and Clinical Applications for Spine Imaging227-233
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Efficient Minimal-Surface Regularization of Perspective Depth Maps in Variational Stereo
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
511-520
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A convex, lower semi-continuous approximation of euler’s elastica energy
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On learning optimized reaction diffusion processes for effective image restoration
International Conference on Computer Vision
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Depth Restoration via Joint Training of a Global Regression Model and CNNs
British Machine Vision Conference
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Bilevel optimization with nonsmooth lower level problems
Proceedings of SSVM 2015
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Learning Reaction-Diffusion Models for Image Inpainting
Pattern Recognition
356-367
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Real-time flare detection in ground-based Ha imaging at Kanzelhöhe Observatory
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iPiasco: Inertial Proximal Algorithm for strongly convex Optimization
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A higher-order MRF based variational model for multiplicative noise reduction
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iPiano: Inertial Proximal Algorithm for Non-Convex Optimization
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Shape from Light Field meets Robust PCA
Computer Vision -- ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VI
751-767
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Interactive 2D/3D Image Denoising and Segmentation Tool for Medical Applications
Proceedings MICCAI Workshop Interactive Medical Image Computation (IMIC)
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Vertebrae Segmentation in 3D CT Images based on a Variational Framework
Proceedings 2nd MICCAI Workshop & Challenge Computational Methods and Clinical Applications in Spine Imaging (CSI)
200-207
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A Deep Variational Model for Image Segmentation
DAGM Symposium Mustererkennung
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Scene Flow Estimation from Light Fields via the Preconditioned Primal-Dual Algorithm
Pattern Recognition: 36th German Conference, GCPR 2014, M{\"u}nster, Germany, September 2-5, 2014, Proceedings
3-14
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An iteratively reweighted Algorithm for Non-smooth Non-convex Optimization in Computer Vision
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Non-Local Total Generalized Variation for Optical Flow Estimation
European Conference on Computer Vision
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Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs
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A bi-level view of inpainting - based image compression
Computer Vision Winter Workshop
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Scale Space and Variational Methods in Computer Vision: 4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, June 2-6, 2013. Proceedings
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Variational Shape from Light Field
Energy Minimization Methods in Computer Vision and Pattern Recognition
66-79
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Revisiting loss-specific training of filter-based MRFs for image restoration
35th German Conference, GCPR 2013, Proceedings
271-281
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Minimizing TGV-Based Variational Models with Non-convex Data Terms
4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, June 2-6, 2013.
282-293
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Dense Reconstruction On-the-Fly
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
1450-1457
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Joint motion estimation and segmentation of complex scenes with label costs and occlusion modeling
Conference on Computer Vision and Pattern Recognition
1878-1885
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Approximate Envelope Minimization for Curvature Regularity
Computer Vision -- ECCV 2012. Workshops and Demonstrations
283-292
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Pushing the Limits of Stereo Using Variational Stereo Estimation
Proceedings of IV 2012
401-407
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Joint 34th DAGM and 36th OAGM Symposium
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Efficient and Globally Optimal Multi View Dense Matching for Aerial Images
Congress / International Society for Photogrammetry and Remote Sensing
227-232
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On paramter learning in variational models
International Symposium on Mathematical Programming
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Learning l1-based analysis and synthesis sparsity priors using bi-level optimization
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Optical Flow Guided TV-L1 Video Interpolation and Restoration
Proceedings of EMMCVPR 2011
273-286
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Diagonal preconditioning for first order primal-dual algorithms in convex optimization
Proceedings of ICCV 2011
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Global Relabeling for Continuous Optimization in Binary Image Segmentation
Proceedings of EMMCVPR 2011
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Online 3D reconstruciton using Convex Optimization
Proceedings of ICCV 2011
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Second Order Total Generalized Variation (TGV) for MRI
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Efficient Minimization of the Non-Local Potts Model
Proceedings of SSVM 2011
314-325
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PROST: Parallel Robust Online Simple Tracking
Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR) 2010
723-730
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Optical flow based deformable volume registration using a novel second-order regularization prior
Proc. SPIE 7623, Medical Imaging 2010: Image Processing
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Aerial Computer Vision for a 3D Virtual Habitat
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A Convex Approach for Variational Super-Resolution
Proceedings of DAGM 2010
313-322
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Variational Segmentation of Elongated Volumetric Structures
IEEE Proceedings of Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2010)
3177-3184
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Total Generalized Variation (TGV) for MRI
2010 Proc. Intl. Soc. Mag. Reson. Med.
4855-4855
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Motion Estimation with Non-Local Total Variation Regularization
Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR) 2010
2464-2471
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Second Order Total Generalized Variation (TGV) for MRI
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Large-Scale Semantic Classification and Ortho-Image Fusion
Proceedings of BMVA Meeting Aerial Image Recognition and Classification 2010
110-114
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Interactive Multi-Label Segmentation
Asian Conference on Computer Vision
392-405
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Fast reduction of undersampling artifacts in radial MR angiography with 3D total variation on graphics hardware
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Point Clouds: Lidar versus 3D Vision
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Exploiting Redundancy for Aerial Image Fusion using Convex Optimization
Proceedings for DAGM 2010
303-312
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Contact
| Thomas Pock | ||
| Inffeldgasse 16/II 8010 Graz, Austria | ||
| mail: pock@icg.tugraz.at phone: +43 316 873-5056 |