Non‐rigid registration computes an alignment between a source surface with a target
surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …

This paper presents a comprehensive literature review on point set registration. The state-of-
the-art modeling methods and algorithms for point set registration are discussed and …

We propose a novel end-to-end deep scene flow model, called PointPWC-Net, that directly
processes 3D point cloud scenes with large motions in a coarse-to-fine fashion. Flow …

Feature matching, which refers to establishing reliable correspondence between two sets of
features (particularly point features), is a critical prerequisite in feature-based registration. In …

This paper solves the problem of nonrigid point set registration by designing a robust
transformation learning scheme. The principle is to iteratively establish point …

Retinal image registration, which can be formulated by matching two sets of sparse features
extracted from two observed retinal images, is a crucial step in the diagnosis and treatment …

We propose a novel end-to-end deep scene flow model, called PointPWC-Net, on 3D point
clouds in a coarse-to-fine fashion. Flow computed at the coarse level is upsampled and …

In order to manipulate a deformable object, such as rope or cloth, in unstructured
environments, robots need a way to estimate its current shape. However, tracking the shape …

This study proposes a novel feature-guided Gaussian mixture model (FG-GMM) for image
matching, which generally requires matching two sets of feature points extracted from the …

Estimating the state of a deformable object is crucial for robotic manipulation, yet accurate
tracking is challenging when the object is partially-occluded. To address this problem, we …