32 citations · 67 across the 10 of their papers we have counts for
11 papers
SemanticSpray++: A Multimodal Dataset for Autonomous Driving in Wet Surface Conditions
Aldi Piroli, Vinzenz Dallabetta, Johannes Kopp +3
Autonomous vehicles rely on camera, LiDAR, and radar sensors to navigate the environment. Adverse weather conditions like snow, rain, and fog are known to be problematic for both c…
Label-Efficient Semantic Segmentation of LiDAR Point Clouds in Adverse Weather Conditions
Aldi Piroli, Vinzenz Dallabetta, Johannes Kopp +3
Adverse weather conditions can severely affect the performance of LiDAR sensors by introducing unwanted noise in the measurements. Therefore, differentiating between noise and vali…
Simultaneous Clutter Detection and Semantic Segmentation of Moving Objects for Automotive Radar Data
Johannes Kopp, Dominik Kellner, Aldi Piroli +2
The unique properties of radar sensors, such as their robustness to adverse weather conditions, make them an important part of the environment perception system of autonomous vehic…
Towards Robust 3D Object Detection In Rainy Conditions
Aldi Piroli, Vinzenz Dallabetta, Johannes Kopp +3
LiDAR sensors are used in autonomous driving applications to accurately perceive the environment. However, they are affected by adverse weather conditions such as snow, fog, and ra…
LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesis
Aldi Piroli, Vinzenz Dallabetta, Johannes Kopp +3
LiDAR-based 3D object detectors have achieved unprecedented speed and accuracy in autonomous driving applications. However, similar to other neural networks, they are often biased…
Energy-based Detection of Adverse Weather Effects in LiDAR Data
Aldi Piroli, Vinzenz Dallabetta, Johannes Kopp +3
Autonomous vehicles rely on LiDAR sensors to perceive the environment. Adverse weather conditions like rain, snow, and fog negatively affect these sensors, reducing their reliabili…