7 accepted papers
In this paper, we present a real-time photo-realistic SLAM method based on marrying Gaussian Splatting with LiDAR-Inertial-Camera SLAM. Most existing radiance-field-based SLAM systems mainly focus on bounded indoor environments, equipped with RGB-D or RGB sensors. However, they are prone to decline
Realistic 3D object and scene reconstruction is pivotal in advancing fields such as world model simulation and embodied intelligence. In this paper, we introduce Hash-GS, a storage-efficient method for large-scale scene reconstruction using anchor-based 3D Gaussian Splatting (3DGS). The vanilla 3DGS
Event cameras have garnered considerable attention due to their advantages over traditional cameras in low power consumption, high dynamic range, and no motion blur. This paper proposes a monocular event-inertial odometry incorporating an adaptive decay kernel-based time surface with polarity-aware…
This letter presents a novel method for geographical localization by registering satellite maps with LiDAR point clouds. This method includes a Transformer-based 2D-3D matching network called D-GLSNet that directly matches the LiDAR point clouds and satellite images through end-to-end learning. With
This paper proposes a LiDAR-Inertial SLAM with efficiently extracted planes, which couples explicit planes in the odometry to improve accuracy and in the mapping for consistency. The proposed method consists of three parts: an efficient Point \boldsymbol{\rightarrow\text{Line}\rightarrow \text{Plane…
Reliable LiDAR panoptic segmentation (LPS), including both semantic and instance segmentation, is vital for many robotic applications, such as autonomous driving. This work proposes a new LPS framework named PANet to eliminate the dependency on the offset branch and improve the performance on large…
This paper proposes an online large-scale dense mapping method for UAVs with a height of 150–250 meters. We first fuse the GPS with the visual odometry to estimate the scaled poses and sparse points. In order to use the depth of sparse points for depth map, we propose Sparse Confidence Cascade View-…