First Author

Frozen Feature Augmentation for Few-Shot Image Classification

Training a linear classifier or lightweight model on top of pretrained vision model outputs, so-called ‘frozen features’, …

Andreas Bär, Neil Houlsby, Mostafa Dehghani, Manoj Kumar

A Novel Benchmark for Refinement of Noisy Localization Labels in Autolabeled Datasets for Object Detection

Autolabeling approaches are attractive w.r.t. time and cost as they allow fast annotation without human intervention. However, can we …

Andreas Bär, Jonas Uhrig, Jeethesh Pai Umesh, Marius Cordts, Tim Fingscheidt

Improvements to Image Reconstruction-Based Performance Prediction for Semantic Segmentation in Highly Automated Driving

The performance of deep neural networks is typically measured with ground truth data which is expensive and not available during …

Andreas Bär, Daniel Kusuma, Tim Fingscheidt

Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder

In supervised learning, a deep neural network’s performance is measured using ground truth data. In semantic segmentation, ground truth …

Andreas Bär, Marvin Klingner, Jonas Löhdefink, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing

Enabling autonomous driving (AD) can be considered one of the biggest challenges in today’s technology. AD is a complex task …

Andreas Bär, Jonas Löhdefink, Nikhil Kapoor, Serin Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

Robust Semantic Segmentation by Redundant Networks With a Layer-Specific Loss Contribution and Majority Vote

The lack of robustness shown by deep neural networks (DNNs) questions their deployment in safety-critical tasks, such as autonomous …

Andreas Bär, Marvin Klingner, Serin Varghese, Fabian Hüger, Peter Schlicht, Tim Fingscheidt

On the Robustness of Redundant Teacher-Student Frameworks for Semantic Segmentation

The trend towards autonomous systems in today’s technology comes with the need for environment perception. Deep neural networks (DNNs) …

Andreas Bär, Fabian Hüger, Peter Schlicht, Tim Fingscheidt