171 citations · 255 across the 4 of their papers we have counts for
12 papers
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…