3D registration with maximal cliques

X Zhang, J Yang, S Zhang… - Proceedings of the IEEE …, 2023‏ - openaccess.thecvf.com
As a fundamental problem in computer vision, 3D point cloud registration (PCR) aims to
seek the optimal pose to align a point cloud pair. In this paper, we present a 3D registration …

Geometric transformer for fast and robust point cloud registration

Z Qin, H Yu, C Wang, Y Guo… - Proceedings of the …, 2022‏ - openaccess.thecvf.com
We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods bypass the detection of repeatable keypoints which is difficult …

Rotation-invariant transformer for point cloud matching

H Yu, Z Qin, J Hou, M Saleh, D Li… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
The intrinsic rotation invariance lies at the core of matching point clouds with handcrafted
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …

Buffer: Balancing accuracy, efficiency, and generalizability in point cloud registration

S Ao, Q Hu, H Wang, K Xu… - Proceedings of the IEEE …, 2023‏ - openaccess.thecvf.com
An ideal point cloud registration framework should have superior accuracy, acceptable
efficiency, and strong generalizability. However, this is highly challenging since existing …

Geotransformer: Fast and robust point cloud registration with geometric transformer

Z Qin, H Yu, C Wang, Y Guo, Y Peng… - … on Pattern Analysis …, 2023‏ - ieeexplore.ieee.org
We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods have shown great potential through bypassing the detection …

Sc2-pcr: A second order spatial compatibility for efficient and robust point cloud registration

Z Chen, K Sun, F Yang, W Tao - Proceedings of the IEEE …, 2022‏ - openaccess.thecvf.com
In this paper, we present a second order spatial compatibility (SC^ 2) measure based
method for efficient and robust point cloud registration (PCR), called SC^ 2-PCR. Firstly, we …

Robust point cloud registration framework based on deep graph matching

K Fu, S Liu, X Luo, M Wang - Proceedings of the IEEE/CVF …, 2021‏ - openaccess.thecvf.com
Abstract 3D point cloud registration is a fundamental problem in computer vision and
robotics. Recently, learning-based point cloud registration methods have made great …

Unsupervised deep probabilistic approach for partial point cloud registration

G Mei, H Tang, X Huang, W Wang… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Deep point cloud registration methods face challenges to partial overlaps and rely on
labeled data. To address these issues, we propose UDPReg, an unsupervised deep …

Lepard: Learning partial point cloud matching in rigid and deformable scenes

Y Li, T Harada - Proceedings of the IEEE/CVF conference …, 2022‏ - openaccess.thecvf.com
Abstract We present Lepard, a Learning based approach for partial point cloud matching in
rigid and deformable scenes. The key characteristics are the following techniques that …

RoReg: Pairwise point cloud registration with oriented descriptors and local rotations

H Wang, Y Liu, Q Hu, B Wang, J Chen… - … on pattern analysis …, 2023‏ - ieeexplore.ieee.org
We present RoReg, a novel point cloud registration framework that fully exploits oriented
descriptors and estimated local rotations in the whole registration pipeline. Previous …