1 code implementation • 14 Feb 2017 • Jan Hendrik Metzen, Tim Genewein, Volker Fischer, Bastian Bischoff
In this work, we propose to augment deep neural networks with a small "detector" subnetwork which is trained on the binary classification task of distinguishing genuine data from data containing adversarial perturbations.
no code implementations • 3 Mar 2017 • Volker Fischer, Mummadi Chaithanya Kumar, Jan Hendrik Metzen, Thomas Brox
Machine learning methods in general and Deep Neural Networks in particular have shown to be vulnerable to adversarial perturbations.
no code implementations • ICCV 2017 • Jan Hendrik Metzen, Mummadi Chaithanya Kumar, Thomas Brox, Volker Fischer
We show empirically that there exist barely perceptible universal noise patterns which result in nearly the same predicted segmentation for arbitrary inputs.
no code implementations • ICLR 2018 • Volker Fischer
Most artificial deep neural networks are partitioned into a directed graph of connected modules or layers and the layers themselves consist of elemental building blocks, such as single units.
1 code implementation • NeurIPS 2018 • Volker Fischer, Jan Köhler, Thomas Pfeil
Deep neural networks, and in particular recurrent networks, are promising candidates to control autonomous agents that interact in real-time with the physical world.
no code implementations • 5 Oct 2018 • Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke
Generating a robust representation of the environment is a crucial ability of learning agents.
no code implementations • 9 Oct 2018 • Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke
Our filter module splits the filter task into multiple less complex and more interpretable subtasks.
no code implementations • 21 Mar 2019 • Lukas Hoyer, Patrick Kesper, Anna Khoreva, Volker Fischer
An environment representation (ER) is a substantial part of every autonomous system.
2 code implementations • NeurIPS 2019 • Lukas Hoyer, Mauricio Munoz, Prateek Katiyar, Anna Khoreva, Volker Fischer
Recently, there has been a growing interest in developing saliency methods that provide visual explanations of network predictions.
no code implementations • 9 Aug 2019 • Chaithanya Kumar Mummadi, Tim Genewein, Dan Zhang, Thomas Brox, Volker Fischer
We achieve state-of-the-art pruning results for ResNet-50 with higher accuracy on ImageNet.
5 code implementations • NeurIPS 2020 • Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling
We introduce the SE(3)-Transformer, a variant of the self-attention module for 3D point clouds and graphs, which is equivariant under continuous 3D roto-translations.
no code implementations • 23 Oct 2020 • Omid Ghahabi, Volker Fischer
This technical report describes the EML submission to the first VoxCeleb speaker diarization challenge.
no code implementations • CVPR 2021 • Jan Bechtold, Maxim Tatarchenko, Volker Fischer, Thomas Brox
Single-view 3D object reconstruction has seen much progress, yet methods still struggle generalizing to novel shapes unseen during training.
no code implementations • ICLR 2021 • Chaithanya Kumar Mummadi, Ranjitha Subramaniam, Robin Hutmacher, Julien Vitay, Volker Fischer, Jan Hendrik Metzen
We conclude that the data augmentation caused by style-variation accounts for the improved corruption robustness and increased shape bias is only a byproduct.
no code implementations • 21 Jun 2021 • Omid Ghahabi, Volker Fischer
Speech Activity Detection (SAD), locating speech segments within an audio recording, is a main part of most speech technology applications.
1 code implementation • ICCV 2021 • Elias Eulig, Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Kilian Rambach, William Beluch, Xiahan Shi, Volker Fischer
We also argue that it is necessary for DNNs to exploit GO to overcome shortcut learning.
1 code implementation • 31 May 2022 • Artem Moskalev, Ivan Sosnovik, Volker Fischer, Arnold Smeulders
The views are ordered in pairs, such that they are either positive, encoding different views of the same object, or negative, corresponding to views of different objects.
1 code implementation • 20 Jul 2022 • Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Claudia Blaiotta, Mauricio Munoz, Volker Fischer
Our approach extends the training set with an additional dataset (the source domain), which is specifically designed to facilitate learning independent representations of basic visual factors.
1 code implementation • 14 Aug 2022 • Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Claudia Blaiotta, Mauricio Munoz, Volker Fischer
While conventional OSR approaches can detect Out-of-Distribution (OOD) samples, they cannot provide explanations indicating which underlying visual attribute(s) (e. g., shape, color or background) cause a specific sample to be unknown.
no code implementations • 12 Sep 2023 • Piyapat Saranrittichai, Mauricio Munoz, Volker Fischer, Chaithanya Kumar Mummadi
We empirically show that our approach improves zero-shot classification results across architectures and datasets, favorably for small objects.
no code implementations • 19 Oct 2023 • David T. Hoffmann, Simon Schrodi, Nadine Behrmann, Volker Fischer, Thomas Brox
In this work, we study rapid, step-wise improvements of the loss in transformers when being confronted with multi-step decision tasks.
no code implementations • 11 Apr 2024 • Simon Schrodi, David T. Hoffmann, Max Argus, Volker Fischer, Thomas Brox
This revealed that the driving factor behind both, the modality gap and the object bias, is the information imbalance between images and captions.