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Found 6 papers, 3 papers with code
LiDAR Snowfall Simulation for Robust 3D Object Detection
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
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather
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
Quantifying Data Augmentation for LiDAR based 3D Object Detection
In this work, we shed light on different data augmentation techniques commonly used in Light Detection and Ranging (LiDAR) based 3D Object Detection.
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
This work addresses the problem of semantic scene understanding under foggy road conditions.
Texture Underfitting for Domain Adaptation
Comprehensive semantic segmentation is one of the key components for robust scene understanding and a requirement to enable autonomous driving.
Simulating Structure-from-Motion
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.
