Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation

Author:

Besic Borna,Gosala NikhilORCID,Cattaneo DanieleORCID,Valada AbhinavORCID

Funder

Federal Ministry of Education and Research (BMBF) of Germany

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Reference25 articles.

1. Minimal-entropy correlation alignment for unsupervised deep domain adaptation;morerio;Proc Int Conf Learn Representations,0

2. Deep CORAL: Correlation Alignment for Deep Domain Adaptation

3. Domain adaptation in LiDAR semantic segmentation by aligning class distributions;alonso;Proc Int Conf Inform Control Automat Robot,0

4. Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds

5. LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation

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1. Panoptic-SLAM: Visual SLAM in Dynamic Environments using Panoptic Segmentation;2024 21st International Conference on Ubiquitous Robots (UR);2024-06-24

2. Fairness and Bias in Robot Learning;Proceedings of the IEEE;2024-04

3. CoVIO: Online Continual Learning for Visual-Inertial Odometry;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

4. Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series;2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2023-01

5. Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learning;Springer Proceedings in Advanced Robotics;2023

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