Short CV

Louis Wiesmann is a PhD student at the Photogrammetry Lab at the University of Bonn since November 2019. He received his master’s degree at the Institute of Geodesy and Geoinformation in 2019.

Research Interests

• SLAM
• Computer Vision
• Machine Learning

Awards

• Turbo-Preis 2019 of the DVW

Publications

2022

• L. Wiesmann, T. Guadagnino, I. Vizzo, G. Grisetti, J. Behley, and C. Stachniss, “DCPCR: Deep Compressed Point Cloud Registration in Large-Scale Outdoor Environments,” Ieee robotics and automation letters (ra-l), vol. 7, iss. 3, pp. 6327-6334, 2022. doi:10.1109/LRA.2022.3171068
  [BibTeX] [PDF]

  @article{wiesmann2022ral-iros,
  author = {L. Wiesmann and T. Guadagnino and I. Vizzo and G. Grisetti and J. Behley and C. Stachniss},
  title = {{DCPCR: Deep Compressed Point Cloud Registration in Large-Scale Outdoor Environments}},
  journal = ral,
  year = 2022,
  volume = 7,
  number = 3,
  pages = {6327-6334},
  issn = {2377-3766},
  doi = {10.1109/LRA.2022.3171068},
  }

• L. Wiesmann, R. Marcuzzi, C. Stachniss, and J. Behley, “Retriever: Point Cloud Retrieval in Compressed 3D Maps,” in Proc.~of the ieee intl.~conf.~on robotics & automation (icra), 2022.
  [BibTeX] [PDF]

  @inproceedings{wiesmann2022icra,
  author = {L. Wiesmann and R. Marcuzzi and C. Stachniss and J. Behley},
  title = {{Retriever: Point Cloud Retrieval in Compressed 3D Maps}},
  booktitle = {Proc.~of the IEEE Intl.~Conf.~on Robotics \& Automation (ICRA)},
  year = 2022,
  }

• R. Marcuzzi, L. Nunes, L. Wiesmann, I. Vizzo, J. Behley, and C. Stachniss, “Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans,” Ieee robotics and automation letters (ra-l), vol. 7, iss. 2, pp. 1550-1557, 2022. doi:10.1109/LRA.2022.3140439
  [BibTeX] [PDF]

  @article{marcuzzi2022ral,
  author = {R. Marcuzzi and L. Nunes and L. Wiesmann and I. Vizzo and J. Behley and C. Stachniss},
  title = {{Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans}},
  journal = ral,
  year = 2022,
  doi = {10.1109/LRA.2022.3140439},
  issn = {2377-3766},
  volume = 7,
  number = 2,
  pages = {1550-1557},
  }

2021

• M. Arora, L. Wiesmann, X. Chen, and C. Stachniss, “Mapping the Static Parts of Dynamic Scenes from 3D LiDAR Point Clouds Exploiting Ground Segmentation,” in Proc. of the european conf. on mobile robots (ecmr), 2021.
  [BibTeX] [PDF] [Code]

  @InProceedings{arora2021ecmr,
  author = {M. Arora and L. Wiesmann and X. Chen and C. Stachniss},
  title = {{Mapping the Static Parts of Dynamic Scenes from 3D LiDAR Point Clouds Exploiting Ground Segmentation}},
  booktitle = ecmr,
  codeurl = {https://github.com/humbletechy/Dynamic-Point-Removal},
  year = {2021},
  }

• X. Chen, S. Li, B. Mersch, L. Wiesmann, J. Gall, J. Behley, and C. Stachniss, “Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data,” Ieee robotics and automation letters (ra-l), vol. 6, pp. 6529-6536, 2021. doi:10.1109/LRA.2021.3093567
  [BibTeX] [PDF] [Code] [Video]

  @article{chen2021ral,
  title={{Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data}},
  author={X. Chen and S. Li and B. Mersch and L. Wiesmann and J. Gall and J. Behley and C. Stachniss},
  year={2021},
  volume=6,
  issue=4,
  pages={6529-6536},
  journal=ral,
  url = {http://www.ipb.uni-bonn.de/pdfs/chen2021ral-iros.pdf},
  codeurl = {https://github.com/PRBonn/LiDAR-MOS},
  videourl = {https://youtu.be/NHvsYhk4dhw},
  doi = {10.1109/LRA.2021.3093567},
  issn = {2377-3766},
  }

• L. Wiesmann, A. Milioto, X. Chen, C. Stachniss, and J. Behley, “Deep Compression for Dense Point Cloud Maps,” Ieee robotics and automation letters (ra-l), vol. 6, pp. 2060-2067, 2021. doi:10.1109/LRA.2021.3059633
  [BibTeX] [PDF] [Code] [Video]

  @article{wiesmann2021ral,
  author = {L. Wiesmann and A. Milioto and X. Chen and C. Stachniss and J. Behley},
  title = {{Deep Compression for Dense Point Cloud Maps}},
  journal = ral,
  volume = 6,
  issue = 2,
  pages = {2060-2067},
  doi = {10.1109/LRA.2021.3059633},
  year = 2021,
  url = {http://www.ipb.uni-bonn.de/pdfs/wiesmann2021ral.pdf},
  codeurl = {https://github.com/PRBonn/deep-point-map-compression},
  videourl = {https://youtu.be/fLl9lTlZrI0}
  }

2020

• C. Stachniss, I. Vizzo, L. Wiesmann, and N. Berning, How To Setup and Run a 100\% Digital Conf.: DIGICROP 2020, 2020.
  [BibTeX] [PDF]
  

  The purpose of this record is to document the setup and execution of DIGICROP 2020 and to simplify conducting future online events of that kind. DIGICROP 2020 was a 100\% virtual conference run via Zoom with around 900 registered people in November 2020. It consisted of video presentations available via our website and a single-day live event for Q&A. We had around 450 people attending the Q&A session overall, most of the time 200-250 people have been online at the same time. This document is a collection of notes, instructions, and todo lists. It is not a polished manual, however, we believe these notes will be useful for other conference organizers and for us in the future.

  @misc{stachniss2020digitalconf,
  author = {C. Stachniss and I. Vizzo and L. Wiesmann and N. Berning},
  title = {{How To Setup and Run a 100\% Digital Conf.: DIGICROP 2020}},
  year = {2020},
  url = {http://www.ipb.uni-bonn.de/pdfs/stachniss2020digitalconf.pdf},
  abstract = {The purpose of this record is to document the setup and execution of DIGICROP 2020 and to simplify conducting future online events of that kind. DIGICROP 2020 was a 100\% virtual conference run via Zoom with around 900 registered people in November 2020. It consisted of video presentations available via our website and a single-day live event for Q&A. We had around 450 people attending the Q&A session overall, most of the time 200-250 people have been online at the same time. This document is a collection of notes, instructions, and todo lists. It is not a polished manual, however, we believe these notes will be useful for other conference organizers and for us in the future.},
  }