9 citations · 14 across the 11 of their papers we have counts for
5 papers · 1 filter
MoPA: Multi-Modal Prior Aided Domain Adaptation for 3D Semantic Segmentation
Haozhi Cao, Yuecong Xu, Jianfei Yang +3
Multi-modal unsupervised domain adaptation (MM-UDA) for 3D semantic segmentation is a practical solution to embed semantic understanding in autonomous systems without expensive poi…
Outram: One-shot Global Localization via Triangulated Scene Graph and Global Outlier Pruning
Pengyu Yin, Haozhi Cao, Thien-Minh Nguyen +4
One-shot LiDAR localization refers to the ability to estimate the robot pose from one single point cloud, which yields significant advantages in initialization and relocalization p…
LIO-GVM: an Accurate, Tightly-Coupled Lidar-Inertial Odometry with Gaussian Voxel Map
Xingyu Ji, Shenghai Yuan, Pengyu Yin +1
This letter presents an accurate and robust Lidar Inertial Odometry framework. We fuse LiDAR scans with IMU data using a tightly-coupled iterative error state Kalman filter for rob…
Segregator: Global Point Cloud Registration with Semantic and Geometric Cues
Pengyu Yin, Shenghai Yuan, Haozhi Cao +3
This paper presents Segregator, a global point cloud registration framework that exploits both semantic information and geometric distribution to efficiently build up outlier-robus…
CoBigICP: Robust and Precise Point Set Registration using Correntropy Metrics and Bidirectional Correspondence
Pengyu Yin, Di Wang, Shaoyi Du +3
In this paper, we propose a novel probabilistic variant of iterative closest point (ICP) dubbed as CoBigICP. The method leverages both local geometrical information and global nois…