Benedikt Mersch

According to our database, Benedikt Mersch authored at least 15 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Clouds.

Matthias Zeller, Vardeep S. Sandhu, Benedikt Mersch, Jens Behley, Michael Heidingsfeld, Cyrill Stachniss

IEEE Trans. Robotics, 2024

Generalizable Stable Points Segmentation for 3D LiDAR Scan-to-Map Long-Term Localization.

Ibrahim Hroob, Benedikt Mersch, Cyrill Stachniss, Marc Hanheide

IEEE Robotics Autom. Lett., 2024

Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion.

Lucas Nunes, Rodrigo Marcuzzi, Benedikt Mersch, Jens Behley, Cyrill Stachniss

CoRR, 2024

2023

KISS-ICP: In Defense of Point-to-Point ICP - Simple, Accurate, and Robust Registration If Done the Right Way.

Ignacio Vizzo, Tiziano Guadagnino, Benedikt Mersch, Louis Wiesmann, Jens Behley, Cyrill Stachniss

IEEE Robotics Autom. Lett., 2023

Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation.

Benedikt Mersch, Tiziano Guadagnino, Xieyuanli Chen, Ignacio Vizzo, Jens Behley, Cyrill Stachniss

IEEE Robotics Autom. Lett., 2023

ERASOR2: Instance-Aware Robust 3D Mapping of the Static World in Dynamic Scenes.

Hyungtae Lim, Lucas Nunes, Benedikt Mersch, Xieyuanli Chen, Jens Behley, Hyun Myung, Cyrill Stachniss

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Toward Reproducible Version-Controlled Perception Platforms: Embracing Simplicity in Autonomous Vehicle Dataset Acquisition.

Ignacio Vizzo, Benedikt Mersch, Lucas Nunes, Louis Wiesmann, Tiziano Guadagnino, Cyrill Stachniss

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Radar Velocity Transformer: Single-scan Moving Object Segmentation in Noisy Radar Point Clouds.

Matthias Zeller, Vardeep S. Sandhu, Benedikt Mersch, Jens Behley, Michael Heidingsfeld, Cyrill Stachniss

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Make it Dense: Self-Supervised Geometric Scan Completion of Sparse 3D LiDAR Scans in Large Outdoor Environments.

Ignacio Vizzo, Benedikt Mersch, Rodrigo Marcuzzi, Louis Wiesmann, Jens Behley, Cyrill Stachniss

IEEE Robotics Autom. Lett., 2022

Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions.

Benedikt Mersch, Xieyuanli Chen, Ignacio Vizzo, Lucas Nunes, Jens Behley, Cyrill Stachniss

IEEE Robotics Autom. Lett., 2022

Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation.

Xieyuanli Chen, Benedikt Mersch, Lucas Nunes, Rodrigo Marcuzzi, Ignacio Vizzo, Jens Behley, Cyrill Stachniss

IEEE Robotics Autom. Lett., 2022

2021

Moving Object Segmentation in 3D LiDAR Data: A Learning-Based Approach Exploiting Sequential Data.

Xieyuanli Chen, Shijie Li, Benedikt Mersch, Louis Wiesmann, Jürgen Gall, Jens Behley, Cyrill Stachniss

IEEE Robotics Autom. Lett., 2021

Maneuver-based Trajectory Prediction for Self-driving Cars Using Spatio-temporal Convolutional Networks.

Benedikt Mersch, Thomas Höllen, Kun Zhao, Cyrill Stachniss, Ribana Roscher

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Embedded Stochastic Field Exploration with Micro Diving Agents using Bayesian Optimization-Guided Tree-Search and GMRFs.

Daniel-André Duecker, Benedikt Mersch, Rene C. Hochdahl, Edwin Kreuzer

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks.

Benedikt Mersch, Xieyuanli Chen, Jens Behley, Cyrill Stachniss

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021