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ORCID8th SSVM 2021: Virtual Event
- Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon:
Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Virtual Event, May 16-20, 2021, Proceedings. Lecture Notes in Computer Science 12679, Springer 2021, ISBN 978-3-030-75548-5
Scale Space and Partial Differential Equations Methods
- Tony Lindeberg
:
Scale-Covariant and Scale-Invariant Gaussian Derivative Networks. 3-14 - Pascal Peter:
Quantisation Scale-Spaces. 15-26 - Remco Duits, Bart M. N. Smets, Erik J. Bekkers, Jim Portegies:
Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations. 27-39 - Jonathan Brokman, Guy Gilboa:
Nonlinear Spectral Processing of Shapes via Zero-Homogeneous Flows. 40-51 - Ido Cohen, Tom Berkov, Guy Gilboa:
Total-Variation Mode Decomposition. 52-64 - Marvin Kahra, Vivek Sridhar, Michael Breuß:
Fast Morphological Dilation and Erosion for Grey Scale Images Using the Fourier Transform. 65-77 - Martin Welk:
Diffusion, Pre-smoothing and Gradient Descent. 78-90 - Mazlum Ferhat Arslan, Sibel Tari:
Local Culprits of Shape Complexity. 91-99 - El Hadji S. Diop, Alioune Mbengue, Bakary Manga, Diaraf Seck:
Extension of Mathematical Morphology in Riemannian Spaces. 100-111
Flow, Motion and Registration
- Noémie Debroux, Carole Le Guyader, Luminita A. Vese:
Multiscale Registration. 115-127 - Ekaterina Sherina, Lisa Krainz, Simon Hubmer, Wolfgang Drexler, Otmar Scherzer:
Challenges for Optical Flow Estimates in Elastography. 128-139 - Lukas Mehl, Cedric Beschle, Andrea Barth, Andrés Bruhn:
An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. 140-152 - Matthieu Pizenberg, Yvain Quéau, Abderrahim Elmoataz:
Low-Rank Registration of Images Captured Under Unknown, Varying Lighting. 153-164 - Alexander Köhler, Michael Breuß:
Towards Efficient Time Stepping for Numerical Shape Correspondence. 165-176 - Sune Darkner, José D. Tascón-Vidarte, François Lauze:
First Order Locally Orderless Registration. 177-188
Optimization Theory and Methods in Imaging
- Jan Plier, Fabrizio Savarino, Michal Kocvara, Stefania Petra:
First-Order Geometric Multilevel Optimization for Discrete Tomography. 191-203 - Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs:
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization. 204-215 - Hari Om Aggrawal, Jan Modersitzki:
Hessian Initialization Strategies for ℓ-BFGS Solving Non-linear Inverse Problems. 216-228 - Danielle Bednarski, Jan Lellmann:
Inverse Scale Space Iterations for Non-convex Variational Problems Using Functional Lifting. 229-241 - Marta Lazzaretti, Simone Rebegoldi, Luca Calatroni, Claudio Estatico:
A Scaled and Adaptive FISTA Algorithm for Signal-Dependent Sparse Image Super-Resolution Problems. 242-253 - Eric B. Gutiérrez, Claire Delplancke, Matthias J. Ehrhardt:
Convergence Properties of a Randomized Primal-Dual Algorithm with Applications to Parallel MRI. 254-266
Machine Learning in Imaging
- Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin:
Wasserstein Generative Models for Patch-Based Texture Synthesis. 269-280 - Hui Shi, Yann Traonmilin, Jean-François Aujol:
Sketched Learning for Image Denoising. 281-293 - Tobias Alt, Pascal Peter, Joachim Weickert, Karl Schrader:
Translating Numerical Concepts for PDEs into Neural Architectures. 294-306 - Leon Bungert, René Raab, Tim Roith, Leo Schwinn, Daniel Tenbrinck:
CLIP: Cheap Lipschitz Training of Neural Networks. 307-319 - Amitoz Azad, Julien Rabin, Abderrahim Elmoataz:
Variational Models for Signal Processing with Graph Neural Networks. 320-332 - Raphaël Achddou, Yann Gousseau, Saïd Ladjal:
Synthetic Images as a Regularity Prior for Image Restoration Neural Networks. 333-345 - Changqing Fu, Laurent D. Cohen:
Geometric Deformation on Objects: Unsupervised Image Manipulation via Conjugation. 346-357 - Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis:
Learning Local Regularization for Variational Image Restoration. 358-370
Segmentation and Labelling
- Bastian Boll, Jonathan Schwarz, Christoph Schnörr:
On the Correspondence Between Replicator Dynamics and Assignment Flows. 373-384 - Alexander Zeilmann, Stefania Petra, Christoph Schnörr:
Learning Linear Assignment Flows for Image Labeling via Exponential Integration. 385-397 - Fabrizio Savarino, Peter Albers, Christoph Schnörr:
On the Geometric Mechanics of Assignment Flows for Metric Data Labeling. 398-410 - Liam Burrows, Ke Chen, Francesco Torella:
A Deep Image Prior Learning Algorithm for Joint Selective Segmentation and Registration. 411-422
Restoration, Reconstruction and Interpolation
- Sarah Andris, Pascal Peter, Rahul Mohideen Kaja Mohideen, Joachim Weickert, Sebastian Hoffmann:
Inpainting-Based Video Compression in FullHD. 425-436 - Martin Huska, Serena Morigi, Giuseppe Antonio Recupero:
Sparsity-Aided Variational Mesh Restoration. 437-449 - Ikram Jumakulyyev, Thomas Schultz:
Lossless PDE-based Compression of 3D Medical Images. 450-462 - Jorge Justiniano, Marko Rajkovic, Martin Rumpf:
Splines for Image Metamorphosis. 463-475 - Monica Pragliola, Luca Calatroni, Alessandro Lanza, Fiorella Sgallari:
Residual Whiteness Principle for Automatic Parameter Selection in ℓ 2-ℓ 2 Image Super-Resolution Problems. 476-488
Inverse Problems in Imaging
- Thomas Pinetz, Erich Kobler, Christian Doberstein, Benjamin Berkels, Alexander Effland:
Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy. 491-502 - Shi Yan, Yiqiu Dong:
GMM Based Simultaneous Reconstruction and Segmentation in X-Ray CT Application. 503-515 - Robert Beinert, Marzieh Hasannasab:
Phase Retrieval via Polarization in Dynamical Sampling. 516-527 - Anna Andrle, Nando Farchmin, Paul Hagemann, Sebastian Heidenreich, Victor Soltwisch, Gabriele Steidl:
Invertible Neural Networks Versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence. 528-539 - Subhadip Mukherjee, Ozan Öktem, Carola-Bibiane Schönlieb:
Adversarially Learned Iterative Reconstruction for Imaging Inverse Problems. 540-552 - Yohann de Castro, Vincent Duval, Romain Petit:
Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems. 553-564 - Kireeti Bodduna, Joachim Weickert, Marcelo Cárdenas:
Multi-frame Super-Resolution from Noisy Data. 565-577
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