Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

Point cloud registration aims to find a rigid transformation for aligning one point cloud to
another. Such registration is a fundamental problem in computer vision and robotics, and …

As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …

PointNet has revolutionized how we think about representing point clouds. For classification
and segmentation tasks, the approach and its subsequent variants/extensions are …

The iterative closest point (ICP) algorithm and its variants are a fundamental technique for
rigid registration between two point sets, with wide applications in different areas from …

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 …

The Iterative Closest Point (ICP) algorithm is one of the most widely used methods for point-
set registration. However, being based on local iterative optimization, ICP is known to be …

PointNet has recently emerged as a popular representation for unstructured point cloud
data, allowing application of deep learning to tasks such as object detection, segmentation …

We present an approach to indoor scene reconstruction from RGB-D video. The key idea is
to combine geometric registration of scene fragments with robust global optimization based …

Data acquisition in large‐scale scenes regularly involves accumulating information across
multiple scans. A common approach is to locally align scan pairs using Iterative Closest …