1 code implementation • CVPR 2022 • Martin Hahner, Christos Sakaridis, Mario Bijelic, Felix Heide, Fisher Yu, Dengxin Dai, Luc van Gool
Due to the difficulty of collecting and annotating training data in this setting, we propose a physically based method to simulate the effect of snowfall on real clear-weather LiDAR point clouds.
Ranked #1 on 3D Object Detection on Heavy Snowfall
1 code implementation • ICCV 2021 • Martin Hahner, Christos Sakaridis, Dengxin Dai, Luc van Gool
2) Through extensive experiments with several state-of-the-art detection approaches, we show that our fog simulation can be leveraged to significantly improve the performance for 3D object detection in the presence of fog.
Ranked #1 on 3D Object Detection on Dense Fog
no code implementations • 3 Apr 2020 • Martin Hahner, Dengxin Dai, Alexander Liniger, Luc van Gool
In this work, we shed light on different data augmentation techniques commonly used in Light Detection and Ranging (LiDAR) based 3D Object Detection.
2 code implementations • 9 Oct 2019 • Martin Hahner, Dengxin Dai, Christos Sakaridis, Jan-Nico Zaech, Luc van Gool
This work addresses the problem of semantic scene understanding under foggy road conditions.
no code implementations • 29 Aug 2019 • Jan-Nico Zaech, Dengxin Dai, Martin Hahner, Luc van Gool
Comprehensive semantic segmentation is one of the key components for robust scene understanding and a requirement to enable autonomous driving.
no code implementations • 3 Oct 2017 • Martin Hahner, Orestis Varesis, Panagiotis Bountouris
The implementation of a Structure-from-Motion (SfM) pipeline from a synthetically generated scene as well as the investigation of the faithfulness of diverse reconstructions is the subject of this project.