Rodrigo Marcuzzi

Orcid: 0000-0001-8076-0293

According to our database1, Rodrigo Marcuzzi authored at least 12 papers between 2022 and 2024.

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

Timeline

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Bibliography

2024
Efficient and Accurate Transformer-Based 3D Shape Completion and Reconstruction of Fruits for Agricultural Robots.
Proceedings of the IEEE International Conference on Robotics and Automation, 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

High Precision Leaf Instance Segmentation for Phenotyping in Point Clouds Obtained Under Real Field Conditions.
IEEE Robotics Autom. Lett., 2023

Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving.
IEEE Robotics Autom. Lett., 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
Make it Dense: Self-Supervised Geometric Scan Completion of Sparse 3D LiDAR Scans in Large Outdoor Environments.
IEEE Robotics Autom. Lett., 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

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

Retriever: Point Cloud Retrieval in Compressed 3D Maps.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022


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