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 …

Given an input set of 3D point pairs the goal of outlier-robust 3D registration is to compute
some rotation and translation that align as many point pairs as possible. This is an important …

For point cloud registration (PCR), a matching matrix is critical. Unfortunately, the existing
approaches do not explicitly devise schemes to refine the matching matrix. Furthermore …

This paper presents a novel non-rigid point set registration method that is inspired by
unsupervised clustering analysis. Unlike previous approaches that treat the source and …

Autonomous driving technology faces significant safety challenges due to the lack of a
global perspective and the limitations of long-range perception capabilities. It is widely …

The extraction of dynamic plant phenotypes is highly important for understanding the
process of plant phenotype formation and formulating growth management plans. Although …

Establishing reliable correspondences is essential for 3D and 2D-3D registration tasks.
Existing methods commonly leverage geometric or semantic point features to generate …

3D point cloud registration is a process of solving the geometric transformation between two
point clouds. This process is an important issue in computer vision and pattern recognition …

Point cloud registration is not only a key step in constructing high-precision 3-D maps, but is
also of great significance in fields such as autonomous navigation, environmental …

Point cloud registration technology, by precisely aligning repair components with the original
artifacts, can accurately record the geometric shape of cultural heritage objects and …