Computational optimal transport: With applications to data science
Optimal transport (OT) theory can be informally described using the words of the French
mathematician Gaspard Monge (1746–1818): A worker with a shovel in hand has to move a …
mathematician Gaspard Monge (1746–1818): A worker with a shovel in hand has to move a …
Comparison of the selected state-of-the-art 3D indoor scanning and point cloud generation methods
Accurate three-dimensional (3D) data from indoor spaces are of high importance for various
applications in construction, indoor navigation and real estate management. Mobile …
applications in construction, indoor navigation and real estate management. Mobile …
Loopreg: Self-supervised learning of implicit surface correspondences, pose and shape for 3d human mesh registration
BL Bhatnagar, C Sminchisescu… - Advances in …, 2020 - proceedings.neurips.cc
We address the problem of fitting 3D human models to 3D scans of dressed humans.
Classical methods optimize both the data-to-model correspondences and the human model …
Classical methods optimize both the data-to-model correspondences and the human model …
Registration of 3D point clouds and meshes: A survey from rigid to nonrigid
Three-dimensional surface registration transforms multiple three-dimensional data sets into
the same coordinate system so as to align overlap** components of these sets. Recent …
the same coordinate system so as to align overlap** components of these sets. Recent …
The wave kernel signature: A quantum mechanical approach to shape analysis
M Aubry, U Schlickewei… - 2011 IEEE international …, 2011 - ieeexplore.ieee.org
We introduce the Wave Kernel Signature (WKS) for characterizing points on non-rigid three-
dimensional shapes. The WKS represents the average probability of measuring a quantum …
dimensional shapes. The WKS represents the average probability of measuring a quantum …
Scalable Gromov-Wasserstein learning for graph partitioning and matching
We propose a scalable Gromov-Wasserstein learning (S-GWL) method and establish a
novel and theoretically-supported paradigm for large-scale graph analysis. The proposed …
novel and theoretically-supported paradigm for large-scale graph analysis. The proposed …
A concise and provably informative multi‐scale signature based on heat diffusion
We propose a novel point signature based on the properties of the heat diffusion process on
a shape. Our signature, called the Heat Kernel Signature (or HKS), is obtained by restricting …
a shape. Our signature, called the Heat Kernel Signature (or HKS), is obtained by restricting …
[BUKU][B] Statistical shape analysis: with applications in R
A thoroughly revised and updated edition of this introduction to modern statistical methods
for shape analysis Shape analysis is an important tool in the many disciplines where objects …
for shape analysis Shape analysis is an important tool in the many disciplines where objects …
Unsupervised learning of dense shape correspondence
We introduce the first completely unsupervised correspondence learning approach for
deformable 3D shapes. Key to our model is the understanding that natural deformations …
deformable 3D shapes. Key to our model is the understanding that natural deformations …
Shape google: Geometric words and expressions for invariant shape retrieval
The computer vision and pattern recognition communities have recently witnessed a surge
of feature-based methods in object recognition and image retrieval applications. These …
of feature-based methods in object recognition and image retrieval applications. These …