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cs.RO2026
Training-Free Target-Aware Refinement of 3D Gaussian Language Map
Sibaek Lee, Kyeongsu Kang, Seongbo Ha +9
Distilling vision-language features into 3D Gaussian Splatting yields a language map that can be queried with arbitrary text. In deployment, however, a small set of user-specified…
cs.RO2026
BayesianGS-SLAM: Uncertainty-Aware Neural Rendering SLAM via Probabilistic Formulation
Kyeongsu Kang, Seongbo Ha, Sibaek Lee +1
Neural-rendering-based SLAM relies on rendered RGB-D residuals for camera tracking and map optimization, but the reliability of these predictions can vary substantially because of…
cs.RO2026
LangGS-SLAM: Real-Time Language-Feature Gaussian Splatting SLAM
Seongbo Ha, Sibaek Lee, Kyungsu Kang +3
In this paper, we propose a RGB-D SLAM system that reconstructs a language-aligned dense feature field while sustaining low-latency tracking and mapping. First, we introduce a Top-…