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9th SSVM 2023: Santa Margherita di Pula, Italy
- Luca Calatroni
, Marco Donatelli
Scale Space and Variational Methods in Computer Vision - 9th International Conference, SSVM 2023, Santa Margherita di Pula, Italy, May 21-25, 2023, Proceedings. Lecture Notes in Computer Science 14009, Springer 2023, ISBN 978-3-031-31974-7
Inverse Problems in Imaging
- Martin Zach
Explicit Diffusion of Gaussian Mixture Model Based Image Priors. 3-15 - Karl Schrader, Pascal Peter, Niklas Kämper, Joachim Weickert:
Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting. 16-28 - Eyal Gofer, Guy Gilboa:
Theoretical Foundations for Pseudo-Inversion of Nonlinear Operators. 29-41 - Michael Quellmalz
A Frame Decomposition of the Funk-Radon Transform. 42-54 - Robert Beinert
Prony-Based Super-Resolution Phase Retrieval of Sparse, Multidimensional Signals. 55-67 - Francesco Colibazzi
Limited Electrodes Models in Electrical Impedance Tomography Reconstruction. 68-80 - Mahipal Jetta
On Trainable Multiplicative Noise Removal Models. 81-93 - Guangyu Cui, Ho Law, Sung Ha Kang:
Surface Reconstruction from Noisy Point Cloud Using Directional G-norm. 94-106 - Francesca Bevilacqua, Yiqiu Dong
Regularized Material Decomposition for K-edge Separation in Hyperspectral Computed Tomography. 107-119 - Laura Girometti
Quaternary Image Decomposition with Cross-Correlation-Based Multi-parameter Selection. 120-133
Machine and Deep Learning in Imaging
- Danielle Bednarski
EmNeF: Neural Fields for Embedded Variational Problems in Imaging. 137-148 - Valentin Penaud-Polge, Santiago Velasco-Forero, Jesús Angulo:
GenHarris-ResNet: A Rotation Invariant Neural Network Based on Elementary Symmetric Polynomials. 149-161 - Hui Shi, Yann Traonmilin, Jean-François Aujol:
Compressive Learning of Deep Regularization for Denoising. 162-174 - Davide Bianchi
Graph Laplacian and Neural Networks for Inverse Problems in Imaging: GraphLaNet. 175-186 - Christina Runkel
Learning Posterior Distributions in Underdetermined Inverse Problems. 187-209 - Johannes Hertrich
Proximal Residual Flows for Bayesian Inverse Problems. 210-222 - Thomas Dagès, Laurent D. Cohen, Alfred M. Bruckstein:
A Model is Worth Tens of Thousands of Examples. 223-235 - Samira Kabri, Tim Roith, Daniel Tenbrinck, Martin Burger:
Resolution-Invariant Image Classification Based on Fourier Neural Operators. 236-249 - Or Streicher, Guy Gilboa:
Graph Laplacian for Semi-supervised Learning. 250-262 - Pierrick Chatillon, Yann Gousseau, Sidonie Lefebvre:
A Geometrically Aware Auto-Encoder for Multi-texture Synthesis. 263-275 - Théo Bertrand
Fast Marching Energy CNN. 276-287 - Saar Huberman, Amit Bracha, Ron Kimmel:
Deep Accurate Solver for the Geodesic Problem. 288-300 - Gaetano Agazzotti, Fabien Pierre, Frédéric Sur
Deep Image Prior Regularized by Coupled Total Variation for Image Colorization. 301-313 - Raphaël Achddou, Yann Gousseau, Saïd Ladjal:
Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras. 314-325 - Abdullah Abdullah, Martin Holler, Karl Kunisch, Malena Sabate Landman:
Latent-Space Disentanglement with Untrained Generator Networks for the Isolation of Different Motion Types in Video Data. 326-338 - Karol Mikula
Natural Numerical Networks on Directed Graphs in Satellite Image Classification. 339-351 - Alessandro Benfenati
Piece-wise Constant Image Segmentation with a Deep Image Prior Approach. 352-362 - Zoé Lambert
On the Inclusion of Topological Requirements in CNNs for Semantic Segmentation Applied to Radiotherapy. 363-375
Optimization for Imaging: Theory and Methods
- Samuel Hurault, Antonin Chambolle, Arthur Leclaire, Nicolas Papadakis:
A Relaxed Proximal Gradient Descent Algorithm for Convergent Plug-and-Play with Proximal Denoiser. 379-392 - Bastien Laville
Off-the-Grid Charge Algorithm for Curve Reconstruction in Inverse Problems. 393-405 - Nathan Buskulic, Yvain Quéau, Jalal Fadili:
Convergence Guarantees of Overparametrized Wide Deep Inverse Prior. 406-417 - Max Kahl
On the Remarkable Efficiency of SMART. 418-430 - Johannes Hertrich
Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line. 431-443 - Shida Wang
A Quasi-Newton Primal-Dual Algorithm with Line Search. 444-456 - Marta Lazzaretti
Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces. 457-470 - Shima Shabani
An Efficient Line Search for Sparse Reconstruction. 471-483 - Lea Bogensperger, Antonin Chambolle, Alexander Effland
Learned Discretization Schemes for the Second-Order Total Generalized Variation. 484-497 - Vasiliki Stergiopoulou, Subhadip Mukherjee, Luca Calatroni, Laure Blanc-Féraud:
Fluctuation-Based Deconvolution in Fluorescence Microscopy Using Plug-and-Play Denoisers. 498-510 - Laura Antonelli
Segmenting MR Images Through Texture Extraction and Multiplicative Components Optimization. 511-521
Scale Space, PDEs, Flow, Motion and Registration
- Nick J. van de Berg, Shuhe Zhang, Bart M. N. Smets, Tos T. J. M. Berendschot
Geodesic Tracking of Retinal Vascular Trees with Optical and TV-Flow Enhancement in SE(2). 525-537 - Gijs Bellaard, Gautam Pai, Javier Oliván Bescós, Remco Duits:
Geometric Adaptations of PDE-G-CNNs. 538-550 - Mara Guastini, Marko Rajkovic
The Variational Approach to the Flow of Sobolev-Diffeomorphisms Model. 551-564 - John M. Ball
Image Comparison and Scaling via Nonlinear Elasticity. 565-574 - Roy Velich, Ron Kimmel:
Learning Differential Invariants of Planar Curves. 575-587 - Kristina Schaefer, Joachim Weickert:
Diffusion-Shock Inpainting. 588-600 - Pascal Peter:
Generalised Scale-Space Properties for Probabilistic Diffusion Models. 601-613 - Florian Beier
Gromov-Wasserstein Transfer Operators. 614-626 - Julie Delon, Agnès Desolneux, Laurent Facq, Arthur Leclaire:
Optimal Transport Between GMM for Multiscale Texture Synthesis. 627-638 - Noémie Debroux
Asymptotic Result for a Decoupled Nonlinear Elasticity-Based Multiscale Registration Model. 639-651 - Paul Bungert, Pascal Peter, Joachim Weickert:
Image Blending with Osmosis. 652-664 - Kouki Tosaka, Atsushi Imiya:
α-Pixels for Hierarchical Analysis of Digital Objects. 665-676 - Ariane Fazeny, Daniel Tenbrinck, Martin Burger:
Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks. 677-690 - Yvain Quéau, Robin Bruneau, Jean Mélou, Jean-Denis Durou, François Lauze:
On Photometric Stereo in the Presence of a Refractive Interface. 691-703 - Lilian Calvet, Nicolas Maignan, Baptiste Brument, Jean Mélou, Silvia Tozza, Jean-Denis Durou, Yvain Quéau:
Multi-view Normal Estimation - Application to Slanted Plane-Sweeping. 704-716 - David Bensaïd, Amit Bracha, Ron Kimmel:
Partial Shape Similarity by Multi-metric Hamiltonian Spectra Matching. 717-729 - Bastian Boll
Modeling Large-Scale Joint Distributions and Inference by Randomized Assignment. 730-742 - Jonathan Schwarz
Quantum State Assignment Flows. 743-756
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