Lucas Nunes

Orcid: 0000-0002-1752-2740

According to our database1, Lucas Nunes authored at least 14 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2022
2023
2024
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3
4
5
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7
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3
5
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3

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Links

On csauthors.net:

Bibliography

2024
Joint Intrinsic and Extrinsic Calibration of Perception Systems Utilizing a Calibration Environment.
IEEE Robotics Autom. Lett., October, 2024

Open-World Semantic Segmentation Including Class Similarity.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences.
IEEE Robotics Autom. Lett., November, 2023

KPPR: Exploiting Momentum Contrast for Point Cloud-Based Place Recognition.
IEEE Robotics Autom. Lett., 2023

Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving.
IEEE Robotics Autom. Lett., 2023

ERASOR2: Instance-Aware Robust 3D Mapping of the Static World in Dynamic Scenes.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Toward Reproducible Version-Controlled Perception Platforms: Embracing Simplicity in Autonomous Vehicle Dataset Acquisition.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Temporal Consistent 3D LiDAR Representation Learning for Semantic Perception in Autonomous Driving.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
SegContrast: 3D Point Cloud Feature Representation Learning Through Self-Supervised Segment Discrimination.
IEEE Robotics Autom. Lett., 2022

Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles.
IEEE Robotics Autom. Lett., 2022

Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions.
IEEE Robotics Autom. Lett., 2022

Contrastive Instance Association for 4D Panoptic Segmentation Using Sequences of 3D LiDAR Scans.
IEEE Robotics Autom. Lett., 2022

Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation.
IEEE Robotics Autom. Lett., 2022


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