5 papers
Graph-GSReg: Leveraging 3D Scene Graphs for Gaussian Splatting Registration
Jaewon Lee, Mangyu Kong, Euntai Kim
Merging multiple 3D Gaussian Splatting (3DGS) scenes into a single unified Gaussian representation is essential for large-scale 3D mapping and long-term map management. Despite its…
Rethinking Pose Refinement in 3D Gaussian Splatting under Pose Prior and Geometric Uncertainty
Mangyu Kong, Jaewon Lee, Seongwon Lee +1
3D Gaussian Splatting (3DGS) has recently emerged as a powerful scene representation and is increasingly used for visual localization and pose refinement. However, despite its high…
Fast Global Localization on Neural Radiance Field
Mangyu Kong, Seongwon Lee, Jaewon Lee +1
Neural Radiance Fields (NeRF) presented a novel way to represent scenes, allowing for high-quality 3D reconstruction from 2D images. Following its remarkable achievements, global l…
GeomGS: LiDAR-Guided Geometry-Aware Gaussian Splatting for Robot Localization
Jaewon Lee, Mangyu Kong, Minseong Park +1
Mapping and localization are crucial problems in robotics and autonomous driving. Recent advances in 3D Gaussian Splatting (3DGS) have enabled precise 3D mapping and scene understa…
DGS-SLAM: Gaussian Splatting SLAM in Dynamic Environment
Mangyu Kong, Jaewon Lee, Seongwon Lee +1
We introduce Dynamic Gaussian Splatting SLAM (DGS-SLAM), the first dynamic SLAM framework built on the foundation of Gaussian Splatting. While recent advancements in dense SLAM hav…