9 citations · 16 across the 5 of their papers we have counts for
5 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…
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…
Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds
Aldi Piroli, Vinzenz Dallabetta, Marc Walessa +3
LiDAR sensors used in autonomous driving applications are negatively affected by adverse weather conditions. One common, but understudied effect, is the condensation of vehicle gas…