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October 13, 2025Open Access

OpenUrban3D: Annotation-Free Open-Vocabulary Semantic Segmentation of Large-Scale Urban Point Clouds

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OpenUrban3D achieves significant improvements in segmentation accuracy and cross-scene generalization.
Experiments indicate robust performance on large-scale urban benchmarks like SensatUrban and SUM.
The framework operates without aligned multi-view images or manual annotations, addressing key challenges.
Zero-shot segmentation allows handling of arbitrary text queries, enhancing flexibility in urban scene understanding.

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Innovative framework improves semantic segmentation accuracy in urban point clouds, suggesting novel applications.

Wang et al. (2025) studied this question.

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