112 citations · 149 across the 5 of their papers we have counts for
6 papers
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Francesco Croce, Sven Gowal, Thomas Brunner +3
Adaptive defenses, which optimize at test time, promise to improve adversarial robustness. We categorize such adaptive test-time defenses, explain their potential benefits and draw…
Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks
Thomas Brunner, Frederik Diehl, Alois Knoll
Many optimization methods for generating black-box adversarial examples have been proposed, but the aspect of initializing said optimizers has not been considered in much detail. W…
Leveraging Semantic Embeddings for Safety-Critical Applications
Thomas Brunner, Frederik Diehl, Michael Truong Le +1
Semantic Embeddings are a popular way to represent knowledge in the field of zero-shot learning. We observe their interpretability and discuss their potential utility in a safety-c…
Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving
Tobias Kessler, Julian Bernhard, Martin Buechel +7
Although many research vehicle platforms for autonomous driving have been built in the past, hardware design, source code and lessons learned have not been made available for the n…
Graph Neural Networks for Modelling Traffic Participant Interaction
Frederik Diehl, Thomas Brunner, Michael Truong Le +1
By interpreting a traffic scene as a graph of interacting vehicles, we gain a flexible abstract representation which allows us to apply Graph Neural Network (GNN) models for traffi…
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks
Thomas Brunner, Frederik Diehl, Michael Truong Le +1
We consider adversarial examples for image classification in the black-box decision-based setting. Here, an attacker cannot access confidence scores, but only the final label. Most…