
-
Nonlinear Spectral Geometry Processing via the TV Transform
We introduce a novel computational framework for digital geometry proces...
read it
-
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Data Poisoning attacks involve an attacker modifying training data to ma...
read it
-
Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction
Machine learning techniques have excelled in the automatic semantic anal...
read it
-
A Simple Domain Shifting Networkfor Generating Low Quality Images
Deep Learning systems have proven to be extremely successful for image r...
read it
-
Generative Models for Generic Light Field Reconstruction
Recently deep generative models have achieved impressive progress in mod...
read it
-
Fast Convex Relaxations using Graph Discretizations
Matching and partitioning problems are fundamentals of computer vision a...
read it
-
Inverting Gradients – How easy is it to break privacy in federated learning?
The idea of federated learning is to collaboratively train a neural netw...
read it
-
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory
We empirically evaluate common assumptions about neural networks that ar...
read it
-
Parametric Majorization for Data-Driven Energy Minimization Methods
Energy minimization methods are a classical tool in a multitude of compu...
read it
-
Controlling Neural Networks via Energy Dissipation
The last decade has shown a tremendous success in solving various comput...
read it
-
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation has been a subject of increased ...
read it
-
Are good local minima wide in sparse recovery?
The idea of compressed sensing is to exploit representations in suitable...
read it
-
Lifting Layers: Analysis and Applications
The great advances of learning-based approaches in image processing and ...
read it
-
Composite Optimization by Nonconvex Majorization-Minimization
Many tasks in imaging can be modeled via the minimization of a nonconvex...
read it
-
Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems
In this work we study convex relaxations of quadratic optimisation probl...
read it
-
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems
While variational methods have been among the most powerful tools for so...
read it
-
Multiframe Motion Coupling for Video Super Resolution
The idea of video super resolution is to use different view points of a ...
read it
-
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies
Convex relaxations of nonconvex multilabel problems have been demonstrat...
read it
-
Sublabel-Accurate Relaxation of Nonconvex Energies
We propose a novel spatially continuous framework for convex relaxations...
read it
-
Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects
We present in this paper the motivation and theory of nonlinear spectral...
read it
-
Point-wise Map Recovery and Refinement from Functional Correspondence
Since their introduction in the shape analysis community, functional map...
read it
-
Variational Depth from Focus Reconstruction
This paper deals with the problem of reconstructing a depth map from a s...
read it
-
The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings
This paper deals with the analysis of a recent reformulation of the prim...
read it