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08/16/2023
SIGMA: Scale-Invariant Global Sparse Shape Matching
We propose a novel mixed-integer programming (MIP) formulation for gener...
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07/18/2023
An Evaluation of Zero-Cost Proxies – from Neural Architecture Performance to Model Robustness
Zero-cost proxies are nowadays frequently studied and used to search for...
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04/28/2023
Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters
The success of deep learning is frequently described as the ability to t...
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04/11/2023
WEAR: A Multimodal Dataset for Wearable and Egocentric Video Activity Recognition
Though research has shown the complementarity of camera- and inertial-ba...
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03/28/2023
CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes
Jointly matching multiple, non-rigidly deformed 3D shapes is a challengi...
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12/14/2022
Convergent Data-driven Regularizations for CT Reconstruction
The reconstruction of images from their corresponding noisy Radon transf...
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10/13/2022
QuAnt: Quantum Annealing with Learnt Couplings
Modern quantum annealers can find high-quality solutions to combinatoria...
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10/05/2022
On Adversarial Robustness of Deep Image Deblurring
Recent approaches employ deep learning-based solutions for the recovery ...
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09/24/2022
A Simple Strategy to Provable Invariance via Orbit Mapping
Many applications require robustness, or ideally invariance, of neural n...
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03/15/2022
Intrinsic Neural Fields: Learning Functions on Manifolds
Neural fields have gained significant attention in the computer vision c...
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10/13/2021
Tutorial on Deep Learning for Human Activity Recognition
Activity recognition systems that are capable of estimating human activi...
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09/29/2021
Stochastic Training is Not Necessary for Generalization
It is widely believed that the implicit regularization of stochastic gra...
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08/12/2021
DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity
Differentiable architecture search (DARTS) is a widely researched tool f...
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08/02/2021
Improving Deep Learning for HAR with shallow LSTMs
Recent studies in Human Activity Recognition (HAR) have shown that Deep ...
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07/13/2021
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields
Dual decomposition approaches in nonconvex optimization may suffer from ...
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07/08/2021
Adiabatic Quantum Graph Matching with Permutation Matrix Constraints
Matching problems on 3D shapes and images are challenging as they are fr...
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06/18/2021
Training or Architecture? How to Incorporate Invariance in Neural Networks
Many applications require the robustness, or ideally the invariance, of ...
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05/06/2021
Q-Match: Iterative Shape Matching via Quantum Annealing
Finding shape correspondences can be formulated as an NP-hard quadratic ...
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02/26/2021
What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors
Data poisoning is a threat model in which a malicious actor tampers with...
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09/07/2020
Nonlinear Spectral Geometry Processing via the TV Transform
We introduce a novel computational framework for digital geometry proces...
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09/04/2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Data Poisoning attacks involve an attacker modifying training data to ma...
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07/01/2020
Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction
Machine learning techniques have excelled in the automatic semantic anal...
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06/30/2020
A Simple Domain Shifting Networkfor Generating Low Quality Images
Deep Learning systems have proven to be extremely successful for image r...
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05/13/2020
Generative Models for Generic Light Field Reconstruction
Recently deep generative models have achieved impressive progress in mod...
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04/23/2020
Fast Convex Relaxations using Graph Discretizations
Matching and partitioning problems are fundamentals of computer vision a...
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03/31/2020
Inverting Gradients – How easy is it to break privacy in federated learning?
The idea of federated learning is to collaboratively train a neural netw...
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10/01/2019
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory
We empirically evaluate common assumptions about neural networks that ar...
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08/17/2019
Parametric Majorization for Data-Driven Energy Minimization Methods
Energy minimization methods are a classical tool in a multitude of compu...
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04/05/2019
Controlling Neural Networks via Energy Dissipation
The last decade has shown a tremendous success in solving various comput...
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07/24/2018
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation has been a subject of increased ...
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06/21/2018
Are good local minima wide in sparse recovery?
The idea of compressed sensing is to exploit representations in suitable...
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03/23/2018
Lifting Layers: Analysis and Applications
The great advances of learning-based approaches in image processing and ...
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02/20/2018
Composite Optimization by Nonconvex Majorization-Minimization
Many tasks in imaging can be modeled via the minimization of a nonconvex...
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11/29/2017
Tighter Lifting-Free Convex Relaxations for Quadratic Matching Problems
In this work we study convex relaxations of quadratic optimisation probl...
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04/11/2017
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems
While variational methods have been among the most powerful tools for so...
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11/23/2016
Multiframe Motion Coupling for Video Super Resolution
The idea of video super resolution is to use different view points of a ...
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04/07/2016
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies
Convex relaxations of nonconvex multilabel problems have been demonstrat...
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12/04/2015
Sublabel-Accurate Relaxation of Nonconvex Energies
We propose a novel spatially continuous framework for convex relaxations...
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10/05/2015
Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects
We present in this paper the motivation and theory of nonlinear spectral...
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06/18/2015
Point-wise Map Recovery and Refinement from Functional Correspondence
Since their introduction in the shape analysis community, functional map...
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08/01/2014
Variational Depth from Focus Reconstruction
This paper deals with the problem of reconstructing a depth map from a s...
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07/07/2014
