176 citations · 336 across the 51 of their papers we have counts for
10 papers · 1 filter
Retail-786k: a Large-Scale Dataset for Visual Entity Matching
Bianca Lamm, Janis Keuper
Entity Matching (EM) defines the task of learning to group objects by transferring semantic concepts from example groups (=entities) to unseen data. Despite the general availabilit…
Don't Look into the Sun: Adversarial Solarization Attacks on Image Classifiers
Paul Gavrikov, Janis Keuper
Assessing the robustness of deep neural networks against out-of-distribution inputs is crucial, especially in safety-critical domains like autonomous driving, but also in safety sy…
On the Interplay of Convolutional Padding and Adversarial Robustness
Paul Gavrikov, Janis Keuper
It is common practice to apply padding prior to convolution operations to preserve the resolution of feature-maps in Convolutional Neural Networks (CNN). While many alternatives ex…
On Invariance, Equivariance, Correlation and Convolution of Spherical Harmonic Representations for Scalar and Vectorial Data
Janis Keuper
The mathematical representations of data in the Spherical Harmonic (SH) domain has recently regained increasing interest in the machine learning community. This technical report gi…
As large as it gets: Learning infinitely large Filters via Neural Implicit Functions in the Fourier Domain
Julia Grabinski, Janis Keuper, Margret Keuper
Recent work in neural networks for image classification has seen a strong tendency towards increasing the spatial context. Whether achieved through large convolution kernels or sel…
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling
Julia Grabinski, Steffen Jung, Janis Keuper +1
Convolutional Neural Networks (CNNs) are successful in various computer vision tasks. From an image and signal processing point of view, this success is counter-intuitive, as the i…
Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality
Peter Lorenz, Ricard Durall, Janis Keuper
Diffusion models recently have been successfully applied for the visual synthesis of strikingly realistic appearing images. This raises strong concerns about their potential for ma…
Fine-Grained Product Classification on Leaflet Advertisements
Daniel Ladwig, Bianca Lamm, Janis Keuper
In this paper, we describe a first publicly available fine-grained product recognition dataset based on leaflet images. Using advertisement leaflets, collected over several years f…
An Extended Study of Human-like Behavior under Adversarial Training
Paul Gavrikov, Janis Keuper, Margret Keuper
Neural networks have a number of shortcomings. Amongst the severest ones is the sensitivity to distribution shifts which allows models to be easily fooled into wrong predictions by…
The Power of Linear Combinations: Learning with Random Convolutions
Paul Gavrikov, Janis Keuper
Following the traditional paradigm of convolutional neural networks (CNNs), modern CNNs manage to keep pace with more recent, for example transformer-based, models by not only incr…