5 papers
Adversarial Vulnerability of Temporal Feature Networks for Object Detection
Svetlana Pavlitskaya, Nikolai Polley, Michael Weber +1
Taking into account information across the temporal domain helps to improve environment perception in autonomous driving. However, it has not been studied so far whether temporally…
Temporal Feature Networks for CNN based Object Detection
Michael Weber, Tassilo Wald, J. Marius Zöllner
For reliable environment perception, the use of temporal information is essential in some situations. Especially for object detection, sometimes a situation can only be understood…
Automated Focal Loss for Image based Object Detection
Michael Weber, Michael Fürst, J. Marius Zöllner
Current state-of-the-art object detection algorithms still suffer the problem of imbalanced distribution of training data over object classes and background. Recent work introduced…
Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps
Florian Piewak, Timo Rehfeld, Michael Weber +1
Grid maps are widely used in robotics to represent obstacles in the environment and differentiating dynamic objects from static infrastructure is essential for many practical appli…
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
Marvin Teichmann, Michael Weber, Marius Zoellner +2
While most approaches to semantic reasoning have focused on improving performance, in this paper we argue that computational times are very important in order to enable real time a…