Open-Vocabulary Segmentation of Aerial Point Clouds
The growing diversity and dynamics of urban environments demand 3D semantic segmentation methods that can recognize a wide range of objects without relying on predefined classes or time-consuming labelled training data. As urban scenes evolve and application requirements vary across locations, flexi...
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| 主要な著者: | , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI AG
2026-02-01
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| シリーズ: | Remote Sensing |
| 主題: | |
| オンライン･アクセス: | https://www.mdpi.com/2072-4292/18/4/572 |
| タグ: |
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