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

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 …

Radar sensors, unlike lidars or cameras, can measure objects' instantaneous velocity and
composition. However, the ability to process and retrieve spatial information from radar point …

Autonomous perception requires high-quality environment sensing in the form of 3D
bounding boxes of dynamic objects. The primary sensors used in automotive systems are …

Localization and perception research for Autonomous Driving is mainly focused on camera
and LiDAR data, rarely on radar data. We apply an automated labeling pipeline to …

Radar sensors are a key component of automated vehicles. The requirements for radar
perception modules are growing more demanding. At the same time, the radar sensors …

The millimeter-wave radar, as an important sensor, is widely used in autonomous driving. In
recent years, to meet the requirement of high level autonomous driving applications …

A major bottleneck to scaling-up training of self-driving perception systems are the human
annotations required for supervision. A promising alternative is to leverage “auto-labelling" …

Automotive radar perception is an integral part of automated driving systems. Radar sensors
benefit from their excellent robustness against adverse weather conditions such as snow …

The performance of perception systems developed for autonomous driving vehicles has
seen significant improvements over the last few years. This improvement was associated …