activity
20192021
most citedIRON: Invariant-based Highly Robust Point Cloud Registration

5 citations · 5 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV2021

Practical, Fast and Robust Point Cloud Registration for 3D Scene Stitching and Object Localization

Lei Sun

3D point cloud registration ranks among the most fundamental problems in remote sensing, photogrammetry, robotics and geometric computer vision. Due to the limited accuracy of 3D f…

cs.CV2021

DANIEL: A Fast and Robust Consensus Maximization Method for Point Cloud Registration with High Outlier Ratios

Lei Sun

Correspondence-based point cloud registration is a cornerstone in geometric computer vision, robotics perception, photogrammetry and remote sensing, which seeks to estimate the bes…

cs.CV2021

Aerial-PASS: Panoramic Annular Scene Segmentation in Drone Videos

Lei Sun, Jia Wang, Kailun Yang +4

Aerial pixel-wise scene perception of the surrounding environment is an important task for UAVs (Unmanned Aerial Vehicles). Previous research works mainly adopt conventional pinhol…

cs.RO2021

ICOS: Efficient and Highly Robust Rotation Search and Point Cloud Registration with Correspondences

Lei Sun

Rotation search and point cloud registration are two fundamental problems in robotics and computer vision, which aim to estimate the rotation and the transformation between the 3D…

cs.CV2021

RANSIC: Fast and Highly Robust Estimation for Rotation Search and Point Cloud Registration using Invariant Compatibility

Lei Sun

Correspondence-based rotation search and point cloud registration are two fundamental problems in robotics and computer vision. However, the presence of outliers, sometimes even oc…

cs.CV20215 cited

IRON: Invariant-based Highly Robust Point Cloud Registration

Lei Sun

In this paper, we present IRON (Invariant-based global Robust estimation and OptimizatioN), a non-minimal and highly robust solution for point cloud registration with a great numbe…