Annotation-free Generation of Training Data Using Mixed Domains for Segmentation of 3D LiDAR Point Clouds
Semantic segmentation is important for robots navigating with 3D LiDARs, but the generation of training datasets requires tedious manual effort. In this paper, we introduce a set of strategies to efficiently generate large datasets by combining real and synthetic data samples. More specifically, the...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2025-09-01
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| Series: | Foundations of Computing and Decision Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/fcds-2025-0013 |
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