171 citations · 244 across the 4 of their papers we have counts for
8 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…
Gated3D: Monocular 3D Object Detection From Temporal Illumination Cues
Frank Julca-Aguilar, Jason Taylor, Mario Bijelic +3
Today's state-of-the-art methods for 3D object detection are based on lidar, stereo, or monocular cameras. Lidar-based methods achieve the best accuracy, but have a large footprint…
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…
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…