1 citations · 1 across the 5 of their papers we have counts for
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…
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…
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…