activity
20202024
most citedEnergy-based Detection of Adverse Weather Effects in LiDAR Data

32 citations · 67 across the 10 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2023★ 32 cited

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…

cs.CV2023

Tackling Clutter in Radar Data -- Label Generation and Detection Using PointNet++

Johannes Kopp, Dominik Kellner, Aldi Piroli +1

Radar sensors employed for environment perception, e.g. in autonomous vehicles, output a lot of unwanted clutter. These points, for which no corresponding real objects exist, are a…