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Technical University of Munich (TUM), Center for Machine Learning (MCML, Karlsruhe Institute of Technology (KIT)
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Ditch ambiguous 2D foundation models: GS4City uses city-model priors to boost semantic Gaussian Splatting, achieving up to 15.8 IoU improvement in coarse building segmentation.
By converting point clouds into a format VLMs can understand, VLM-Loc significantly boosts text-to-point-cloud localization accuracy, outperforming prior methods that rely on shallower text-point cloud correspondences.
