2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
Real-Time LiDAR Gaussian Splatting SLAM
Seungjun Tak, Yewon Jeon, Jaeik Hwang +3
We present a real-time LiDAR-based framework for Gaussian Splatting SLAM that tightly couples fast G-ICP registration with spherical rasterization-based dense mapping for large-sca…
GSO-SLAM: Bidirectionally Coupled Gaussian Splatting and Direct Visual Odometry
Jiung Yeon, Seongbo Ha, Hyeonwoo Yu
We propose GSO-SLAM, a real-time monocular dense SLAM system that leverages Gaussian scene representation. Unlike existing methods that couple tracking and mapping with a unified s…
LEGO-SLAM: Language-Embedded Gaussian Optimization SLAM
Sibaek Lee, Seongbo Ha, Kyeongsu Kang +3
Recent advances in 3D Gaussian Splatting (3DGS) have enabled Simultaneous Localization and Mapping (SLAM) systems to build photorealistic maps. However, these maps lack the open-vo…
Bayesian NeRF: Quantifying Uncertainty with Volume Density for Neural Implicit Fields
Sibeak Lee, Kyeongsu Kang, Seongbo Ha +1
We present a Bayesian Neural Radiance Field (NeRF), which explicitly quantifies uncertainty in the volume density by modeling uncertainty in the occupancy, without the need for add…
RGBD GS-ICP SLAM
Seongbo Ha, Jiung Yeon, Hyeonwoo Yu
Simultaneous Localization and Mapping (SLAM) with dense representation plays a key role in robotics, Virtual Reality (VR), and Augmented Reality (AR) applications. Recent advanceme…