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 …

We present a novel representation of maps between pairs of shapes that allows for efficient
inference and manipulation. Key to our approach is a generalization of the notion of map …

We review methods designed to compute correspondences between geometric shapes
represented by triangle meshes, contours or point sets. This survey is motivated in part by …

We present a simple and efficient method for refining maps or correspondences by iterative
upsampling in the spectral domain that can be implemented in a few lines of code. Our main …

This paper presents a comprehensive review and analysis of recent spectral shape
descriptors for nonrigid 3D shape retrieval. More specifically, we compare the latest spectral …

The goal of our work is to develop an efficient, automatic algorithm for discovering point
correspondences between surfaces that are approximately and/or partially isometric. Our …

A common operation in many geometry processing algorithms consists of finding
correspondences between pairs of shapes by finding structure‐preserving maps between …

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 …

Point cloud registration is a fundamental task in computer graphics, and more specifically, in
rigid and non-rigid shape matching. The rigid shape matching problem can be formulated as …

We review the computation of 3D geometric data mapping, which establishes one-to-one
correspondence between or among spatial/spatiotemporal objects. Effective mapping …