A Simple Framework of Few-Shot Learning Using Sparse Annotations for Semantic Segmentation of 3-D Point Clouds
The semantic segmentation of point clouds plays a crucial role in the interpretation of 3-D scene. However, the majority of supervised learning methods needs a great number of annotated data to train an effective model, which requires labor-intensive and time-consuming annotation of 3-D points. In t...
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| Autors principals: | , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
IEEE
2024-01-01
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| Col·lecció: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Matèries: | |
| Accés en línia: | https://ieeexplore.ieee.org/document/10423773/ |
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