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ORCID10th SSVM 2025: Dartington, UK - Part I
- Tatiana A. Bubba
, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb:
Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part I. Lecture Notes in Computer Science 15667, Springer 2025, ISBN 978-3-031-92365-4
Inverse Problems in Imaging
- Carole Le Guyader, Fabien Pierre:
Contrast Highlighting of TV-Based Reconstructed Polarimetric Images. 3-15 - Robert Beinert, Jonas Bresch:
Denoising Hyperbolic-Valued Data by Relaxed Regularizations. 16-29 - Mohammad Sadegh Salehi, Tatiana A. Bubba, Yury Korolev:
Fast Inexact Bilevel Optimization for Analytical Deep Image Priors. 30-42 - Evangelos Papoutsellis, Zeljko Kereta, Kostas Papafitsoros:
Why do we Regularise in Every Iteration for Imaging Inverse Problems? 43-55 - Matthias Beckmann, Carla Dittert:
On an Analytical Inversion Formula for the Modulo Radon Transform. 56-69 - Tommi Heikkilä:
MultiResolution Low-Rank Regularization of Dynamic Imaging Problems. 70-82 - Stefano Aleotti, Marco Donatelli, Rolf Krause, Pietro Maurino:
A Fractional Graph La+$\varPsi $ Approach to Image Reconstruction. 83-95 - Padmaja Yinukula, Mahipal Jetta, Rajkumar Alugunuri, Sarita Panda, Meraj Alam:
A Fractional-Order Telegraph Diffusion Model for Multiplicative Noise Removal. 96-107 - Jasper M. Everink, Bernardin Tamo Amougou, Marcelo Pereyra:
Self-supervised Conformal Prediction for Uncertainty Quantification in Imaging Problems. 108-118 - Roy Y. He, Han Wang:
Real-Time Scene Recovery from Image Scale Space and Perceptual Hue Similarity. 119-131 - Richard Huber:
A Novel Interpretation of the Radon Transform's Ray and Pixel-Driven Discretizations Under Balanced Resolutions. 132-145 - Laurenz Nagler, Martin Zach, Thomas Pock:
Product of Gaussian Mixture Diffusion Model for Non-linear MRI Inversion. 146-158 - Monica Pragliola, Luca Calatroni, Alessandro Lanza:
Whiteness-Based Bilevel Estimation of Weighted TV Parameter Maps for Image Denoising. 159-172 - Jonathan Krook, Willem Diepeveen, Ozan Öktem:
Direct Atomistic Reconstruction in Homogeneous Cryo-EM Using Protein Geometry Regularization. 173-184 - Naïl Khelifa, Carola-Bibiane Schönlieb, Ferdia Sherry:
Enhanced Denoising and Convergent Regularisation Using Tweedie Scaling. 185-197
Machine and Deep Learning in Imaging
- Ali Joundi, Yann Traonmilin, Alasdair Newson:
Max-Sparsity Atomic Autoencoders with Application to Inverse Problems. 201-213 - Andreas Decker, Alexander Effland, Erich Kobler:
Equivariant Bootstrap for Uncertainty Quantification in Image Classification. 214-226 - Marien Renaud, Arthur Leclaire, Nicolas Papadakis:
Equivariant Denoisers for Image Restoration. 227-240 - Matthias Beckmann, Robert Beinert, Jonas Bresch:
Max-Normalized Radon Cumulative Distribution Transform for Limited Data Classification. 241-254 - Quentin Rapilly, Anaïs Badoual, Pierre Maindron, Guenaelle Bouet, Charles Kervrann:
Prediction of Parametric Surfaces for Multi-object Segmentation in 3D Biological Imaging. 255-268 - Alexander Denker, Johannes Hertrich, Zeljko Kereta, Silvia Cipiccia, Ecem Erin, Simon R. Arridge:
Plug-and-Play Half-Quadratic Splitting for Ptychography. 269-281 - Thanh Trung Vu, Andreas Kofler, Kostas Papafitsoros:
Deep Unrolling for Learning Optimal Spatially Varying Regularisation Parameters for Total Generalised Variation. 282-294 - Jonathan Brokman, Amit Giloni, Omer Hofman, Roman Vainshtein, Hisashi Kojima, Guy Gilboa:
Identifying Memorization of Diffusion Models Through p-Laplace Analysis. 295-307 - Nicolas Makaroff, Théo Bertrand, Laurent D. Cohen:
Learning Anisotropic Metrics for Geodesic Distances via the Heat Equation for Image Segmentation. 308-321 - Lucas Beerens, Catherine F. Higham, Desmond J. Higham:
Deceptive Diffusion: Generating Synthetic Adversarial Examples. 322-333 - Tatiana A. Bubba, Matteo Santacesaria, Andrea Sebastiani:
TomoSelfDEQ: Self-supervised Deep Equilibrium Learning for Sparse-Angle CT Reconstruction. 334-346 - Mohammad Sadegh Salehi, Subhadip Mukherjee, Lindon Roberts, Matthias J. Ehrhardt:
Bilevel Learning with Inexact Stochastic Gradients. 347-359 - Michael Adipoetra, Ségolène Martin:
Deep Generative Clustering with VAEs and Expectation-Maximization. 360-373 - Paul Hagemann, Janina Schütte, David Sommer, Martin Eigel, Gabriele Steidl:
Sampling from Boltzmann Densities with Physics Informed Low-Rank Formats. 374-386 - Laura Girometti, Jean-François Aujol, Antoine Guennec, Yann Traonmilin:
Parameter-Free Structure-Texture Image Decomposition by Unrolling. 387-399 - Sven Dummer, Puru Vaish, Christoph Brune:
Joint Manifold Learning and Optimal Transport for Dynamic Imaging. 400-411
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