6 citations · 17 across the 6 of their papers we have counts for
6 papers
Semantics-Guided Moving Object Segmentation with 3D LiDAR
Shuo Gu, Suling Yao, Jian Yang +1
Moving object segmentation (MOS) is a task to distinguish moving objects, e.g., moving vehicles and pedestrians, from the surrounding static environment. The segmentation accuracy…
Unsupervised Visible-light Images Guided Cross-Spectrum Depth Estimation from Dual-Modality Cameras
Yubin Guo, Haobo Jiang, Xinlei Qi +3
Cross-spectrum depth estimation aims to provide a depth map in all illumination conditions with a pair of dual-spectrum images. It is valuable for autonomous vehicle applications w…
Globally Optimal Relative Pose Estimation with Gravity Prior
Yaqing Ding, Daniel Barath, Jian Yang +2
Smartphones, tablets and camera systems used, e.g., in cars and UAVs, are typically equipped with IMUs (inertial measurement units) that can measure the gravity vector accurately.…
Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration
Zezhou Sun, Banghe Wu, Cheng-Zhong Xu +3
We propose an integrated approach to active exploration by exploiting the Cartographer method as the base SLAM module for submap creation and performing efficient frontier detectio…
Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation
Mingmei Cheng, Le Hui, Jin Xie +2
In this paper, we propose a cascaded non-local neural network for point cloud segmentation. The proposed network aims to build the long-range dependencies of point clouds for the a…
LiDAR Iris for Loop-Closure Detection
Ying Wang, Zezhou Sun, Cheng-Zhong Xu +3
In this paper, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for fast and accurate loop-closure detection. A binary signature image can be obtained fo…