Volker Fischer

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Does enhanced shape bias improve neural network robustness to common corruptions?

Convolutional neural networks (CNNs) learn to extract representations of...
04/20/2021 ∙ by Chaithanya Kumar Mummadi, et al. ∙ 0 ∙ share

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Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors

Single-view 3D object reconstruction has seen much progress, yet methods...
04/01/2021 ∙ by Jan Bechtold, et al. ∙ 0 ∙ share

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EML System Description for VoxCeleb Speaker Diarization Challenge 2020

This technical report describes the EML submission to the first VoxCeleb...
10/23/2020 ∙ by Omid Ghahabi, et al. ∙ 0 ∙ share

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SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

We introduce the SE(3)-Transformer, a variant of the self-attention modu...
06/18/2020 ∙ by Fabian B. Fuchs, et al. ∙ 1 ∙ share

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Group Pruning using a Bounded-Lp norm for Group Gating and Regularization

Deep neural networks achieve state-of-the-art results on several tasks w...
08/09/2019 ∙ by Chaithanya Kumar Mummadi, et al. ∙ 0 ∙ share

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Grid Saliency for Context Explanations of Semantic Segmentation

Recently, there has been a growing interest in developing saliency metho...
07/30/2019 ∙ by Lukas Hoyer, et al. ∙ 5 ∙ share

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Short-Term Prediction and Multi-Camera Fusion on Semantic Grids

An environment representation (ER) is a substantial part of every autono...
03/21/2019 ∙ by Lukas Hoyer, et al. ∙ 4 ∙ share

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Functionally Modular and Interpretable Temporal Filtering for Robust Segmentation

The performance of autonomous systems heavily relies on their ability to...
10/09/2018 ∙ by Jörg Wagner, et al. ∙ 2 ∙ share

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Hierarchical Recurrent Filtering for Fully Convolutional DenseNets

Generating a robust representation of the environment is a crucial abili...
10/05/2018 ∙ by Jörg Wagner, et al. ∙ 0 ∙ share

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The streaming rollout of deep networks - towards fully model-parallel execution

Deep neural networks, and in particular recurrent networks, are promisin...
06/13/2018 ∙ by Volker Fischer, et al. ∙ 0 ∙ share

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Universal Adversarial Perturbations Against Semantic Image Segmentation

While deep learning is remarkably successful on perceptual tasks, it was...
04/19/2017 ∙ by Jan-Hendrik Metzen, et al. ∙ 0 ∙ share

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Adversarial Examples for Semantic Image Segmentation

Machine learning methods in general and Deep Neural Networks in particul...
03/03/2017 ∙ by Volker Fischer, et al. ∙ 0 ∙ share

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On Detecting Adversarial Perturbations

Machine learning and deep learning in particular has advanced tremendous...
02/14/2017 ∙ by Jan-Hendrik Metzen, et al. ∙ 0 ∙ share

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Volker Fischer

Featured Co-authors

Max Welling

Sven Behnke

Thomas Brox

Jan-Hendrik Metzen

Dan Zhang

Anna Khoreva

Tim Genewein

Daniel E. Worrall

Maxim Tatarchenko

Michael Herman

Jörg Wagner

Does enhanced shape bias improve neural network robustness to common corruptions?

Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors

EML System Description for VoxCeleb Speaker Diarization Challenge 2020

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

Group Pruning using a Bounded-Lp norm for Group Gating and Regularization

Grid Saliency for Context Explanations of Semantic Segmentation

Short-Term Prediction and Multi-Camera Fusion on Semantic Grids

Functionally Modular and Interpretable Temporal Filtering for Robust Segmentation

Hierarchical Recurrent Filtering for Fully Convolutional DenseNets

The streaming rollout of deep networks - towards fully model-parallel execution

Universal Adversarial Perturbations Against Semantic Image Segmentation

Adversarial Examples for Semantic Image Segmentation

On Detecting Adversarial Perturbations