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Optimal Sensor Data Fusion Architecture for Object Detection in Adverse
  Weather Conditions

Optimal Sensor Data Fusion Architecture for Object Detection in Adverse Weather Conditions

6 July 2018
Andreas Pfeuffer
Klaus C. J. Dietmayer
ArXivPDFHTML

Papers citing "Optimal Sensor Data Fusion Architecture for Object Detection in Adverse Weather Conditions"

7 / 7 papers shown
Title
Survey on LiDAR Perception in Adverse Weather Conditions
Survey on LiDAR Perception in Adverse Weather Conditions
M. Dreissig
Dominik Scheuble
Florian Piewak
Joschka Boedecker
26
31
0
13 Apr 2023
An Unsupervised Domain Adaptive Approach for Multimodal 2D Object
  Detection in Adverse Weather Conditions
An Unsupervised Domain Adaptive Approach for Multimodal 2D Object Detection in Adverse Weather Conditions
George Eskandar
Robert A. Marsden
Pavithran Pandiyan
Mario Döbler
Karim Guirguis
B. Yang
28
7
0
07 Mar 2022
DSOR: A Scalable Statistical Filter for Removing Falling Snow from LiDAR
  Point Clouds in Severe Winter Weather
DSOR: A Scalable Statistical Filter for Removing Falling Snow from LiDAR Point Clouds in Severe Winter Weather
Akhil M Kurup
J. Bos
19
62
0
15 Sep 2021
Multimodal End-to-End Learning for Autonomous Steering in Adverse Road
  and Weather Conditions
Multimodal End-to-End Learning for Autonomous Steering in Adverse Road and Weather Conditions
Jyri Maanpää
Josef Taher
P. Manninen
Leo Pakola
Iaroslav Melekhov
Juha Hyyppa
20
15
0
28 Oct 2020
Multimodal End-to-End Autonomous Driving
Multimodal End-to-End Autonomous Driving
Yi Xiao
Felipe Codevilla
A. Gurram
O. Urfalioglu
Antonio M. López
19
241
0
07 Jun 2019
Deep Multi-modal Object Detection and Semantic Segmentation for
  Autonomous Driving: Datasets, Methods, and Challenges
Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
Di Feng
Christian Haase-Schuetz
Lars Rosenbaum
Heinz Hertlein
Claudius Gläser
Fabian Duffhauss
W. Wiesbeck
Klaus C. J. Dietmayer
3DPC
41
989
0
21 Feb 2019
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural
  Network For Lidar 3D Vehicle Detection
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection
Di Feng
Lars Rosenbaum
Klaus C. J. Dietmayer
3DPC
UQCV
36
243
0
13 Apr 2018
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