
Learning Sparse Masks for Diffusionbased Image Inpainting
Diffusionbased inpainting is a powerful tool for the reconstruction of ...
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Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods
Partial differential equation (PDE) models and their associated variatio...
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Connections between Numerical Algorithms for PDEs and Neural Networks
We investigate numerous structural connections between numerical algorit...
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Translating Numerical Concepts for PDEs into Neural Architectures
We investigate what can be learned from translating numerical algorithms...
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Multiframe Superresolution from Noisy Data
Obtaining high resolution images from low resolution data with clipped n...
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Learning Integrodifferential Models for Image Denoising
We introduce an integrodifferential extension of the edgeenhancing anis...
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PDE Evolutions for MSmoothers in One, Two, and Three Dimensions
Local Msmoothers are interesting and important signal and image process...
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Translating Diffusion, Wavelets, and Regularisation into Residual Networks
Convolutional neural networks (CNNs) often perform well, but their stabi...
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Robustness of Brain Tumor Segmentation
We address the generalization behavior of deep neural networks in the co...
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Variational Coupling Revisited: Simpler Models, Theoretical Connections, and Novel Applications
Variational models with coupling terms are becoming increasingly popular...
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Learning a Generic Adaptive Wavelet Shrinkage Function for Denoising
The rise of machine learning in image processing has created a gap betwe...
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Object Segmentation Tracking from Generic Video Cues
We propose a lightweight variational framework for online tracking of o...
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Stable Backward Diffusion Models that Minimise Convex Energies
Backward diffusion processes appear naturally in image enhancement and d...
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Algorithms for Piecewise Constant Signal Approximations
We consider the problem of finding optimal piecewise constant approximat...
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SpaceFilling Curve Indices as Acceleration Structure for ExemplarBased Inpainting
Exemplarbased inpainting is the process of reconstructing missing parts...
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Optimising Spatial and Tonal Data for PDEbased Inpainting
Some recent methods for lossy signal and image compression store only a ...
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Joachim Weickert
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Professor of Mathematics and Computer Science at Saarland University, Head of Mathematical Image Analysis Group at Saarland University, Research Assistant at the University of Kaiserslautern, PostDoctoral Researcher at the Universities of Utrecht and Copenhagen, Assistant professor at the University of Mannheim.