Search Results for author: Stefanie Walz

Found 5 papers, 1 papers with code

ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering

no code implementations ICCV 2023 Andrea Ramazzina, Mario Bijelic, Stefanie Walz, Alessandro Sanvito, Dominik Scheuble, Felix Heide

With data as bottleneck and most of today's training data relying on good weather conditions with inclement weather as outlier, we rely on an inverse rendering approach to reconstruct the scene content.

Autonomous Vehicles Inverse Rendering +1

Gated2Gated: Self-Supervised Depth Estimation from Gated Images

1 code implementation CVPR 2022 Amanpreet Walia, Stefanie Walz, Mario Bijelic, Fahim Mannan, Frank Julca-Aguilar, Michael Langer, Werner Ritter, Felix Heide

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.

Depth Estimation

A Benchmark for Spray from Nearby Cutting Vehicles

no code implementations24 Aug 2021 Stefanie Walz, Mario Bijelic, Florian Kraus, Werner Ritter, Martin Simon, Igor Doric

Current driver assistance systems and autonomous driving stacks are limited to well-defined environment conditions and geo fenced areas.

Autonomous Driving Benchmarking

Uncertainty depth estimation with gated images for 3D reconstruction

no code implementations11 Mar 2020 Stefanie Walz, Tobias Gruber, Werner Ritter, Klaus Dietmayer

Gated imaging is an emerging sensor technology for self-driving cars that provides high-contrast images even under adverse weather influence.

3D Reconstruction Depth Completion +2

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