UTTO uses uncertainty to guide test-time optimization with foundation model priors to enhance depth-only open-vocabulary 3D semantic segmentation without training, outperforming baselines on ScanNet datasets.
Openurban3d: Label-free open-vocabulary semantic seg- mentation of large-scale urban point clouds.IEEE Transac- tions on Geoscience and Remote Sensing, 64:4501917, 2026
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Privacy-Preserving Depth-Only Open-Vocabulary 3D Semantic Segmentation Via Uncertainty-Guided Test-Time Optimization
UTTO uses uncertainty to guide test-time optimization with foundation model priors to enhance depth-only open-vocabulary 3D semantic segmentation without training, outperforming baselines on ScanNet datasets.