148 citations · 415 across the 10 of their papers we have counts for
10 papers
The Radar Ghost Dataset -- An Evaluation of Ghost Objects in Automotive Radar Data
Florian Kraus, Nicolas Scheiner, Werner Ritter +1
Radar sensors have a long tradition in advanced driver assistance systems (ADAS) and also play a major role in current concepts for autonomous vehicles. Their importance is reasone…
RadarScenes: A Real-World Radar Point Cloud Data Set for Automotive Applications
Ole Schumann, Markus Hahn, Nicolas Scheiner +4
A new automotive radar data set with measurements and point-wise annotations from more than four hours of driving is presented. Data provided by four series radar sensors mounted o…
Using Machine Learning to Detect Ghost Images in Automotive Radar
Florian Kraus, Nicolas Scheiner, Werner Ritter +1
Radar sensors are an important part of driver assistance systems and intelligent vehicles due to their robustness against all kinds of adverse conditions, e.g., fog, snow, rain, or…
Off-the-shelf sensor vs. experimental radar -- How much resolution is necessary in automotive radar classification?
Nicolas Scheiner, Ole Schumann, Florian Kraus +3
Radar-based road user detection is an important topic in the context of autonomous driving applications. The resolution of conventional automotive radar sensors results in a sparse…
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar
Nicolas Scheiner, Florian Kraus, Fangyin Wei +8
Conventional sensor systems record information about directly visible objects, whereas occluded scene components are considered lost in the measurement process. Non-line-of-sight (…
A Multi-Stage Clustering Framework for Automotive Radar Data
Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann +1
Radar sensors provide a unique method for executing environmental perception tasks towards autonomous driving. Especially their capability to perform well in adverse weather condit…