225 citations · 738 across the 12 of their papers we have counts for
15 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…
Simulating Road Spray Effects in Automotive Lidar Sensor Models
Clemens Linnhoff, Dominik Scheuble, Mario Bijelic +5
Modeling perception sensors is key for simulation based testing of automated driving functions. Beyond weather conditions themselves, sensors are also subjected to object dependent…
Gated2Gated: Self-Supervised Depth Estimation from Gated Images
Amanpreet Walia, Stefanie Walz, Mario Bijelic +5
Gated cameras hold promise as an alternative to scanning LiDAR sensors with high-resolution 3D depth that is robust to back-scatter in fog, snow, and rain. Instead of sequentially…
A Benchmark for Spray from Nearby Cutting Vehicles
Stefanie Walz, Mario Bijelic, Florian Kraus +3
Current driver assistance systems and autonomous driving stacks are limited to well-defined environment conditions and geo fenced areas. To increase driving safety in adverse weath…
ZeroScatter: Domain Transfer for Long Distance Imaging and Vision through Scattering Media
Zheng Shi, Ethan Tseng, Mario Bijelic +2
Adverse weather conditions, including snow, rain, and fog, pose a major challenge for both human and computer vision. Handling these environmental conditions is essential for safe…
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…
Uncertainty depth estimation with gated images for 3D reconstruction
Stefanie Walz, Tobias Gruber, Werner Ritter +1
Gated imaging is an emerging sensor technology for self-driving cars that provides high-contrast images even under adverse weather influence. It has been shown that this technology…
A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?
Mario Bijelic, Tobias Gruber, Werner Ritter
Autonomous driving at level five does not only means self-driving in the sunshine. Adverse weather is especially critical because fog, rain, and snow degrade the perception of the…
Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving
Mario Bijelic, Tobias Gruber, Werner Ritter
Adverse weather conditions are very challenging for autonomous driving because most of the state-of-the-art sensors stop working reliably under these conditions. In order to develo…
Learning Super-resolved Depth from Active Gated Imaging
Tobias Gruber, Mariia Kokhova, Werner Ritter +2
Environment perception for autonomous driving is doomed by the trade-off between range-accuracy and resolution: current sensors that deliver very precise depth information are usua…
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 (…
Weather Influence and Classification with Automotive Lidar Sensors
Robin Heinzler, Philipp Schindler, Jürgen Seekircher +2
Lidar sensors are often used in mobile robots and autonomous vehicles to complement camera, radar and ultrasonic sensors for environment perception. Typically, perception algorithm…
Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios
Tobias Gruber, Mario Bijelic, Felix Heide +2
This work introduces an evaluation benchmark for depth estimation and completion using high-resolution depth measurements with angular resolution of up to 25" (arcsecond), akin to…
Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather
Mario Bijelic, Tobias Gruber, Fahim Mannan +4
The fusion of multimodal sensor streams, such as camera, lidar, and radar measurements, plays a critical role in object detection for autonomous vehicles, which base their decision…
Gated2Depth: Real-time Dense Lidar from Gated Images
Tobias Gruber, Frank Julca-Aguilar, Mario Bijelic +3
We present an imaging framework which converts three images from a gated camera into high-resolution depth maps with depth accuracy comparable to pulsed lidar measurements. Existin…