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Louis Wiesmann
Louis Wiesmann
Photogrammetry & Robotics Lab, University of Bonn
Verified email at igg.uni-bonn.de
Title
Cited by
Cited by
Year
Moving object segmentation in 3D LiDAR data: A learning-based approach exploiting sequential data
X Chen, S Li, B Mersch, L Wiesmann, J Gall, J Behley, C Stachniss
IEEE Robotics and Automation Letters 6 (4), 6529-6536, 2021
1462021
Kiss-icp: In defense of point-to-point icp–simple, accurate, and robust registration if done the right way
I Vizzo, T Guadagnino, B Mersch, L Wiesmann, J Behley, C Stachniss
IEEE Robotics and Automation Letters 8 (2), 1029-1036, 2023
1122023
Deep compression for dense point cloud maps
L Wiesmann, A Milioto, X Chen, C Stachniss, J Behley
IEEE Robotics and Automation Letters 6 (2), 2060-2067, 2021
632021
Robust onboard localization in changing environments exploiting text spotting
N Zimmerman, L Wiesmann, T Guadagnino, T Läbe, J Behley, ...
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
232022
Mapping the static parts of dynamic scenes from 3D LiDAR point clouds exploiting ground segmentation
M Arora, L Wiesmann, X Chen, C Stachniss
2021 European Conference on Mobile Robots (ECMR), 1-6, 2021
222021
Retriever: Point cloud retrieval in compressed 3D maps
L Wiesmann, R Marcuzzi, C Stachniss, J Behley
2022 International Conference on Robotics and Automation (ICRA), 10925-10932, 2022
212022
Mask-based panoptic lidar segmentation for autonomous driving
R Marcuzzi, L Nunes, L Wiesmann, J Behley, C Stachniss
IEEE Robotics and Automation Letters 8 (2), 1141-1148, 2023
202023
Contrastive instance association for 4d panoptic segmentation using sequences of 3d lidar scans
R Marcuzzi, L Nunes, L Wiesmann, I Vizzo, J Behley, C Stachniss
IEEE Robotics and Automation Letters 7 (2), 1550-1557, 2022
182022
Static map generation from 3D LiDAR point clouds exploiting ground segmentation
M Arora, L Wiesmann, X Chen, C Stachniss
Robotics and Autonomous Systems 159, 104287, 2023
122023
Locndf: Neural distance field mapping for robot localization
L Wiesmann, T Guadagnino, I Vizzo, N Zimmerman, Y Pan, H Kuang, ...
IEEE Robotics and Automation Letters, 2023
112023
Temporal consistent 3d lidar representation learning for semantic perception in autonomous driving
L Nunes, L Wiesmann, R Marcuzzi, X Chen, J Behley, C Stachniss
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
112023
KPPR: Exploiting momentum contrast for point cloud-based place recognition
L Wiesmann, L Nunes, J Behley, C Stachniss
IEEE Robotics and Automation Letters 8 (2), 592-599, 2022
82022
Make it dense: Self-supervised geometric scan completion of sparse 3d lidar scans in large outdoor environments
I Vizzo, B Mersch, R Marcuzzi, L Wiesmann, J Behley, C Stachniss
IEEE Robotics and Automation Letters 7 (3), 8534-8541, 2022
72022
Dcpcr: Deep compressed point cloud registration in large-scale outdoor environments
L Wiesmann, T Guadagnino, I Vizzo, G Grisetti, J Behley, C Stachniss
IEEE Robotics and Automation Letters 7 (3), 6327-6334, 2022
72022
High precision leaf instance segmentation for phenotyping in point clouds obtained under real field conditions
E Marks, M Sodano, F Magistri, L Wiesmann, D Desai, R Marcuzzi, ...
IEEE Robotics and Automation Letters, 2023
62023
PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency
Y Pan, X Zhong, L Wiesmann, T Posewsky, J Behley, C Stachniss
arXiv preprint arXiv:2401.09101, 2024
32024
Lio-ekf: High frequency lidar-inertial odometry using extended kalman filters
Y Wu, T Guadagnino, L Wiesmann, L Klingbeil, C Stachniss, H Kuhlmann
arXiv preprint arXiv:2311.09887, 2023
12023
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences
R Marcuzzi, L Nunes, L Wiesmann, E Marks, J Behley, C Stachniss
IEEE Robotics and Automation Letters, 2023
12023
Toward Reproducible Version-Controlled Perception Platforms: Embracing Simplicity in Autonomous Vehicle Dataset Acquisition
I Vizzo, B Mersch, L Nunes, L Wiesmann, T Guadagnino, C Stachniss
2023 IEEE 26th International Conference on Intelligent Transportation …, 2023
2023
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