17 citations · 18 across the 2 of their papers we have counts for
6 papers
REGTR: End-to-end Point Cloud Correspondences with Transformers
Zi Jian Yew, Gim Hee Lee
Despite recent success in incorporating learning into point cloud registration, many works focus on learning feature descriptors and continue to rely on nearest-neighbor feature ma…
Learning Iterative Robust Transformation Synchronization
Zi Jian Yew, Gim Hee Lee
Transformation Synchronization is the problem of recovering absolute transformations from a given set of pairwise relative motions. Despite its usefulness, the problem remains chal…
City-scale Scene Change Detection using Point Clouds
Zi Jian Yew, Gim Hee Lee
We propose a method for detecting structural changes in a city using images captured from vehicular mounted cameras over traversals at two different times. We first generate 3D poi…
RPM-Net: Robust Point Matching using Learned Features
Zi Jian Yew, Gim Hee Lee
Iterative Closest Point (ICP) solves the rigid point cloud registration problem iteratively in two steps: (1) make hard assignments of spatially closest point correspondences, and…
Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes
Ziquan Lan, Zi Jian Yew, Gim Hee Lee
Outlier feature matches and loop-closures that survived front-end data association can lead to catastrophic failures in the back-end optimization of large-scale point cloud based 3…
3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration
Zi Jian Yew, Gim Hee Lee
In this paper, we propose the 3DFeat-Net which learns both 3D feature detector and descriptor for point cloud matching using weak supervision. Unlike many existing works, we do not…