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.
Scal- ing open-vocabulary image segmentation with image-level labels
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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.