Lucas Nunes

PhD Student
Contact:
Email: lucas.nunes@nulligg.uni-bonn.de
Tel: +49 – 228 – 73 – 29 05
Fax: +49 – 228 – 73 – 27 12
Office: Nussallee 15, 1. OG, room 1.003
Address:
University of Bonn
Photogrammetry, IGG
Nussallee 15
53115 Bonn

Profiles: Google Scholar | ResearchGate | LinkedIn

Research Interests

  • Autonomous Vehicles
  • Representation Learning
  • Self-Supervised Learning
  • Computer Vision

Short CV

Lucas Nunes is a Ph.D. student at the University of Bonn. He received a Bachelor’s degree in Computer Science and a Master’s degree in Robotics from the University of São Paulo, Brazil, in 2018 and 2020, respectively. During his Master’s he spent three months at Karlsruher Institut für Technologie as an internship student. His Master’s thesis was focused on Depth Estimation of Occluded Regions.

Code releases

Publications

2024

  • M. Sodano, F. Magistri, L. Nunes, J. Behley, and C. Stachniss, “Open-World Semantic Segmentation Including Class Similarity,” in Proc. of the IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), 2024.
    [BibTeX] [PDF] 
    @inproceedings{sodano2024cvpr,
author = {M. Sodano and F. Magistri and L. Nunes and J. Behley and C. Stachniss},
title = {{Open-World Semantic Segmentation Including Class Similarity}},
booktitle = cvpr,
year = 2024,
}
  • L. Nunes, R. Marcuzzi, B. Mersch, J. Behley, and C. Stachniss, “Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion,” in Proc. of the IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), 2024.
    [BibTeX] [PDF] [Code] 
    @inproceedings{nunes2024cvpr,
author = {L. Nunes and R. Marcuzzi and B. Mersch and J. Behley and C. Stachniss},
title = {{Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion}},
booktitle = cvpr,
year = 2024,
codeurl = {https://github.com/PRBonn/LiDiff},
}

2023

  • R. Marcuzzi, L. Nunes, L. Wiesmann, E. Marks, J. Behley, and C. Stachniss, “Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences,” IEEE Robotics and Automation Letters (RA-L), vol. 8, iss. 11, pp. 7487-7494, 2023. doi:10.1109/LRA.2023.3320020
    [BibTeX] [PDF] [Code] [Video] 
    @article{marcuzzi2023ral-meem,
author = {R. Marcuzzi and L. Nunes and L. Wiesmann and E. Marks and J. Behley and C. Stachniss},
title = {{Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences}},
journal = ral,
year = {2023},
volume = {8},
number = {11},
pages = {7487-7494},
issn = {2377-3766},
doi = {10.1109/LRA.2023.3320020},
codeurl = {https://github.com/PRBonn/Mask4D},
videourl = {https://youtu.be/4WqK_gZlpfA},
}
  • I. Vizzo, B. Mersch, L. Nunes, L. Wiesmann, T. Guadagnino, and C. Stachniss, “Toward Reproducible Version-Controlled Perception Platforms: Embracing Simplicity in Autonomous Vehicle Dataset Acquisition,” in Proc. of the Intl. Conf. on Intelligent Transportation Systems Workshops, 2023.
    [BibTeX] [PDF] [Code] 
    @inproceedings{vizzo2023itcsws,
author = {I. Vizzo and B. Mersch and L. Nunes and L. Wiesmann and T. Guadagnino and C. Stachniss},
title = {{Toward Reproducible Version-Controlled Perception Platforms: Embracing Simplicity in Autonomous Vehicle Dataset Acquisition}},
booktitle = {Proc. of the Intl. Conf. on Intelligent Transportation Systems Workshops},
year = 2023,
codeurl = {https://github.com/ipb-car/meta-workspace},
note = {accepted}
}
  • H. Lim, L. Nunes, B. Mersch, X. Chen, J. Behley, H. Myung, and C. Stachniss, “ERASOR2: Instance-Aware Robust 3D Mapping of the Static World in Dynamic Scenes,” in Proc. of Robotics: Science and Systems (RSS), 2023.
    [BibTeX] [PDF] 
    @inproceedings{lim2023rss,
author = {H. Lim and L. Nunes and B. Mersch and X. Chen and J. Behley and H. Myung and C. Stachniss},
title = {{ERASOR2: Instance-Aware Robust 3D Mapping of the Static World in Dynamic Scenes}},
booktitle = rss,
year = 2023,
}
  • L. Nunes, L. Wiesmann, R. Marcuzzi, X. Chen, J. Behley, and C. Stachniss, “Temporal Consistent 3D LiDAR Representation Learning for Semantic Perception in Autonomous Driving,” in Proc. of the IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), 2023.
    [BibTeX] [PDF] [Code] [Video] 
    @inproceedings{nunes2023cvpr,
author = {L. Nunes and L. Wiesmann and R. Marcuzzi and X. Chen and J. Behley and C. Stachniss},
title = {{Temporal Consistent 3D LiDAR Representation Learning for Semantic Perception in Autonomous Driving}},
booktitle = cvpr,
year = 2023,
codeurl = {https://github.com/PRBonn/TARL},
videourl = {https://youtu.be/0CtDbwRYLeo},
}
  • R. Marcuzzi, L. Nunes, L. Wiesmann, J. Behley, and C. Stachniss, “Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving,” IEEE Robotics and Automation Letters (RA-L), vol. 8, iss. 2, p. 1141–1148, 2023. doi:10.1109/LRA.2023.3236568
    [BibTeX] [PDF] [Video] 
    @article{marcuzzi2023ral,
author = {R. Marcuzzi and L. Nunes and L. Wiesmann and J. Behley and C. Stachniss},
title = {{Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving}},
journal = ral,
volume = {8},
number = {2},
pages = {1141--1148},
year = 2023,
doi = {10.1109/LRA.2023.3236568},
videourl = {https://youtu.be/I8G9VKpZux8}
}
  • L. Wiesmann, L. Nunes, J. Behley, and C. Stachniss, “KPPR: Exploiting Momentum Contrast for Point Cloud-Based Place Recognition,” IEEE Robotics and Automation Letters (RA-L), vol. 8, iss. 2, pp. 592-599, 2023. doi:10.1109/LRA.2022.3228174
    [BibTeX] [PDF] [Code] [Video] 
    @article{wiesmann2023ral,
author = {L. Wiesmann and L. Nunes and J. Behley and C. Stachniss},
title = {{KPPR: Exploiting Momentum Contrast for Point Cloud-Based Place Recognition}},
journal = ral,
volume = {8},
number = {2},
pages = {592-599},
year = 2023,
issn = {2377-3766},
doi = {10.1109/LRA.2022.3228174},
codeurl = {https://github.com/PRBonn/kppr},
videourl = {https://youtu.be/bICz1sqd8Xs}
}

2022

  • L. Nunes, X. Chen, R. Marcuzzi, A. Osep, L. Leal-Taixé, C. Stachniss, and J. Behley, “Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles,” IEEE Robotics and Automation Letters (RA-L), 2022. doi:10.1109/LRA.2022.3187872
    [BibTeX] [PDF] [Code] [Video] 
    @article{nunes2022ral-3duis,
author = {Lucas Nunes and Xieyuanli Chen and Rodrigo Marcuzzi and Aljosa Osep and Laura Leal-Taixé and Cyrill Stachniss and Jens Behley},
title = {{Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles}},
journal = ral,
url = {https://www.ipb.uni-bonn.de/pdfs/nunes2022ral-iros.pdf},
codeurl = {https://github.com/PRBonn/3DUIS},
videourl= {https://youtu.be/cgv0wUaqLAE},
doi = {10.1109/LRA.2022.3187872},
year = 2022
}
  • B. Mersch, X. Chen, I. Vizzo, L. Nunes, J. Behley, and C. Stachniss, “Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions,” IEEE Robotics and Automation Letters (RA-L), vol. 7, iss. 3, p. 7503–7510, 2022. doi:10.1109/LRA.2022.3183245
    [BibTeX] [PDF] [Code] [Video] 
    @article{mersch2022ral,
author = {B. Mersch and X. Chen and I. Vizzo and L. Nunes and J. Behley and C. Stachniss},
title = {{Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions}},
journal = ral,
year = 2022,
url = {https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/mersch2022ral.pdf},
volume = {7},
number = {3},
pages = {7503--7510},
doi = {10.1109/LRA.2022.3183245},
codeurl = {https://github.com/PRBonn/4DMOS},
videourl = {https://youtu.be/5aWew6caPNQ},
}
  • X. Chen, B. Mersch, L. Nunes, R. Marcuzzi, I. Vizzo, J. Behley, and C. Stachniss, “Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation,” IEEE Robotics and Automation Letters (RA-L), vol. 7, iss. 3, pp. 6107-6114, 2022. doi:10.1109/LRA.2022.3166544
    [BibTeX] [PDF] [Code] [Video] 
    @article{chen2022ral,
author = {X. Chen and B. Mersch and L. Nunes and R. Marcuzzi and I. Vizzo and J. Behley and C. Stachniss},
title = {{Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation}},
journal = ral,
year = 2022,
volume = 7,
number = 3,
pages = {6107-6114},
url = {https://arxiv.org/pdf/2201.04501},
issn = {2377-3766},
doi = {10.1109/LRA.2022.3166544},
codeurl = {https://github.com/PRBonn/auto-mos},
videourl = {https://youtu.be/3V5RA1udL4c},
}
  • L. Nunes, R. Marcuzzi, X. Chen, J. Behley, and C. Stachniss, “SegContrast: 3D Point Cloud Feature Representation Learning through Self-supervised Segment Discrimination,” IEEE Robotics and Automation Letters (RA-L), vol. 7, iss. 2, pp. 2116-2123, 2022. doi:10.1109/LRA.2022.3142440
    [BibTeX] [PDF] [Code] [Video] 
    @article{nunes2022ral,
author = {L. Nunes and R. Marcuzzi and X. Chen and J. Behley and C. Stachniss},
title = {{SegContrast: 3D Point Cloud Feature Representation Learning through Self-supervised Segment Discrimination}},
journal = ral,
year = 2022,
doi = {10.1109/LRA.2022.3142440},
issn = {2377-3766},
volume = {7},
number = {2},
pages = {2116-2123},
url = {https://www.ipb.uni-bonn.de/pdfs/nunes2022ral-icra.pdf},
codeurl = {https://github.com/PRBonn/segcontrast},
videourl = {https://youtu.be/kotRb_ySnIw},
}
  • 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},
}