
Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physicsinformed neural networks
Electroanatomical maps are a key tool in the diagnosis and treatment of ...
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GEASI: Geodesicbased Earliest Activation Sites Identification in cardiac models
The personalization of cardiac models is the cornerstone of patientspec...
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Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction
Recent deep learning approaches focus on improving quantitative scores o...
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Shared Prior Learning of EnergyBased Models for Image Reconstruction
We propose a novel learningbased framework for image reconstruction par...
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BPMVSNet: BeliefPropagationLayers for MultiViewStereo
In this work, we propose BPMVSNet, a convolutional neural network (CNN)...
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Total Deep Variation: A Stable Regularizer for Inverse Problems
Various problems in computer vision and medical imaging can be cast as i...
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Belief Propagation Reloaded: Learning BPLayers for Labeling Problems
It has been proposed by many researchers that combining deep neural netw...
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Total Deep Variation for Linear Inverse Problems
Diverse inverse problems in imaging can be cast as variational problems ...
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The Five Elements of Flow
In this work we propose five concrete steps to improve the performance o...
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Image Morphing in Deep Feature Spaces: Theory and Applications
This paper combines image metamorphosis with deep features. To this end,...
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On the estimation of the Wasserstein distance in generative models
Generative Adversarial Networks (GANs) have been used to model the under...
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Learned Collaborative Stereo Refinement
In this work, we propose a learningbased method to denoise and refine d...
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SelfSupervised Learning for Stereo Reconstruction on Aerial Images
Recent developments established deep learning as an inevitable tool to b...
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An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration
We investigate a wellknown phenomenon of variational approaches in imag...
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Fast Decomposable Submodular Function Minimization using Constrained Total Variation
We consider the problem of minimizing the sum of submodular set function...
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ConvexConcave Backtracking for Inertial Bregman Proximal Gradient Algorithms in NonConvex Optimization
Backtracking linesearch is an old yet powerful strategy for finding bet...
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Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction
Following the success of deep learning in a wide range of applications, ...
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Learning Energy Based Inpainting for Optical Flow
Modern optical flow methods are often composed of a cascade of many inde...
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3D Fluid Flow Estimation with Integrated Particle Reconstruction
The standard approach to densely reconstruct the motion in a volume of f...
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Variational 3DPIV with Sparse Descriptors
3D Particle Imaging Velocimetry (3DPIV) aim to recover the flow field i...
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Robust Deformation Estimation in WoodComposite Materials using Variational Optical Flow
Woodcomposite materials are widely used today as they homogenize humidi...
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Semantic 3D Reconstruction with Finite Element Bases
We propose a novel framework for the discretisation of multilabel probl...
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Scalable Full Flow with Learned Binary Descriptors
We propose a method for large displacement optical flow in which local m...
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Learning a Variational Network for Reconstruction of Accelerated MRI Data
Purpose: To allow fast and highquality reconstruction of clinical accel...
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RealTime Panoramic Tracking for Event Cameras
Event cameras are a paradigm shift in camera technology. Instead of full...
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EndtoEnd Training of Hybrid CNNCRF Models for Stereo
We propose a novel and principled hybrid CNN+CRF model for stereo estima...
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Solving Dense Image Matching in RealTime using DiscreteContinuous Optimization
Dense image matching is a fundamental lowlevel problem in Computer Visi...
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On learning optimized reaction diffusion processes for effective image restoration
For several decades, image restoration remains an active research topic ...
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Total variation on a tree
We consider the problem of minimizing the continuous valued total variat...
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A higherorder MRF based variational model for multiplicative noise reduction
The Fields of Experts (FoE) image prior model, a filterbased higherord...
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iPiano: Inertial Proximal Algorithm for NonConvex Optimization
In this paper we study an algorithm for solving a minimization problem c...
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A bilevel view of inpainting  based image compression
Inpainting based image compression approaches, especially linear and non...
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Revisiting lossspecific training of filterbased MRFs for image restoration
It is now well known that Markov random fields (MRFs) are particularly e...
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Learning ℓ_1based analysis and synthesis sparsity priors using bilevel optimization
We consider the analysis operator and synthesis dictionary learning prob...
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Insights into analysis operator learning: From patchbased sparse models to higherorder MRFs
This paper addresses a new learning algorithm for the recently introduce...
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A Convex Approach for Image Hallucination
In this paper we propose a global convex approach for image hallucinatio...
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Filament and Flare Detection in Hα image sequences
Solar storms can have a major impact on the infrastructure of the earth....
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Thomas Pock
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PhD (20052008) in Computer Engineering (Telematik) from Graz University of Technology, Postdoc position at the University of Bonn, Assistant Professor at the Institute for Computer Graphics and Vision at Graz University of Technology, START price of the Austrian Science Fund (FWF) 2013, German Pattern recognition award of the German association for pattern recognition (DAGM) and in 2014, Professor of Computer Science at Graz University of Technology (AIT Stiftungsprofessur "Mobile Computer Vision") and a principal scientist at the Center for Vision, Automation & Control at the Austrian Institute of Technology (AIT).