13 citations · 20 across the 15 of their papers we have counts for
16 papers
From Codebooks to VLMs: Evaluating Automated Visual Discourse Analysis for Climate Change on Social Media
Katharina Prasse, Steffen Jung, Isaac Bravo +4
Social media platforms have become primary arenas for climate communication, generating millions of images and posts that - if systematically analysed - can reveal which communicat…
TRIX- Trading Adversarial Fairness via Mixed Adversarial Training
Tejaswini Medi, Steffen Jung, Margret Keuper
Adversarial Training (AT) is a widely adopted defense against adversarial examples. However, existing approaches typically apply a uniform training objective across all classes, ov…
Corner Cases: How Size and Position of Objects Challenge ImageNet-Trained Models
Mishal Fatima, Steffen Jung, Margret Keuper
Backgrounds in images play a major role in contributing to spurious correlations among different data points. Owing to aesthetic preferences of humans capturing the images, dataset…
Deep Learning for Climate Action: Computer Vision Analysis of Visual Narratives on X
Katharina Prasse, Marcel Kleinmann, Inken Adam +8
Climate change is one of the most pressing challenges of the 21st century, sparking widespread discourse across social media platforms. Activists, policymakers, and researchers see…
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
Tejaswini Medi, Steffen Jung, Margret Keuper
Deep neural networks are susceptible to adversarial attacks and common corruptions, which undermine their robustness. In order to enhance model resilience against such challenges,…
Can We Talk Models Into Seeing the World Differently?
Paul Gavrikov, Jovita Lukasik, Steffen Jung +4
Unlike traditional vision-only models, vision language models (VLMs) offer an intuitive way to access visual content through language prompting by combining a large language model…
Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
Katharina Prasse, Steffen Jung, Yuxuan Zhou +1
Hand action recognition is essential. Communication, human-robot interactions, and gesture control are dependent on it. Skeleton-based action recognition traditionally includes han…
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…
Neural Architecture Design and Robustness: A Dataset
Steffen Jung, Jovita Lukasik, Margret Keuper
Deep learning models have proven to be successful in a wide range of machine learning tasks. Yet, they are often highly sensitive to perturbations on the input data which can lead…
Happy People -- Image Synthesis as Black-Box Optimization Problem in the Discrete Latent Space of Deep Generative Models
Steffen Jung, Jan Christian Schwedhelm, Claudia Schillings +1
In recent years, optimization in the learned latent space of deep generative models has been successfully applied to black-box optimization problems such as drug design, image gene…
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
Shashank Agnihotri, Steffen Jung, Margret Keuper
While neural networks allow highly accurate predictions in many tasks, their lack of robustness towards even slight input perturbations often hampers their deployment. Adversarial…
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
Steffen Jung, Margret Keuper
The minimum cost multicut problem is the NP-hard/APX-hard combinatorial optimization problem of partitioning a real-valued edge-weighted graph such as to minimize the total cost of…
FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting
Julia Grabinski, Steffen Jung, Janis Keuper +1
Over the last years, Convolutional Neural Networks (CNNs) have been the dominating neural architecture in a wide range of computer vision tasks. From an image and signal processing…
Learning Where To Look -- Generative NAS is Surprisingly Efficient
Jovita Lukasik, Steffen Jung, Margret Keuper
The efficient, automated search for well-performing neural architectures (NAS) has drawn increasing attention in the recent past. Thereby, the predominant research objective is to…
Optimizing Edge Detection for Image Segmentation with Multicut Penalties
Steffen Jung, Sebastian Ziegler, Amirhossein Kardoost +1
The Minimum Cost Multicut Problem (MP) is a popular way for obtaining a graph decomposition by optimizing binary edge labels over edge costs. While the formulation of a MP from ind…
Spectral Distribution Aware Image Generation
Steffen Jung, Margret Keuper
Recent advances in deep generative models for photo-realistic images have led to high quality visual results. Such models learn to generate data from a given training distribution…