SEM-GAT: explainable semantic pose estimation using learned graph attention
This paper proposes a Graph Neural Network (GNN)-based method for exploiting semantics and local geometry to guide the identification of reliable pointcloud registration candidates. Semantic and morphological features of the environment serve as key reference points for registration, enabling accura...
| Main Authors: | , , , , |
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| 格式: | Conference item |
| 語言: | English |
| 出版: |
IEEE
2024
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