A survey of optimal transport for computer graphics and computer vision
Optimal transport is a long‐standing theory that has been studied in depth from both
theoretical and numerical point of views. Starting from the 50s this theory has also found a …
theoretical and numerical point of views. Starting from the 50s this theory has also found a …
Wasserstein iterative networks for barycenter estimation
Wasserstein barycenters have become popular due to their ability to represent the average
of probability measures in a geometrically meaningful way. In this paper, we present an …
of probability measures in a geometrically meaningful way. In this paper, we present an …
Fixed support tree-sliced Wasserstein barycenter
The Wasserstein barycenter has been widely studied in various fields, including natural
language processing, and computer vision. However, it requires a high computational cost …
language processing, and computer vision. However, it requires a high computational cost …
Impus: Image morphing with perceptually-uniform sampling using diffusion models
We present a diffusion-based image morphing approach with perceptually-uniform sampling
(IMPUS) that produces smooth, direct, and realistic interpolations given an image pair. A …
(IMPUS) that produces smooth, direct, and realistic interpolations given an image pair. A …
Distributed optimization with quantization for computing wasserstein barycenters
R Krawtschenko, CA Uribe, A Gasnikov… - arXiv preprint arXiv …, 2020 - arxiv.org
We study the problem of the decentralized computation of entropy-regularized semi-discrete
Wasserstein barycenters over a network. Building upon recent primal-dual approaches, we …
Wasserstein barycenters over a network. Building upon recent primal-dual approaches, we …
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
Optimal transport (OT) barycenters are a mathematically grounded way of averaging
probability distributions while capturing their geometric properties. In short, the barycenter …
probability distributions while capturing their geometric properties. In short, the barycenter …
When and how can deep generative models be inverted?
Deep generative models (eg GANs and VAEs) have been developed quite extensively in
recent years. Lately, there has been an increased interest in the inversion of such a model …
recent years. Lately, there has been an increased interest in the inversion of such a model …
An integer program for pricing support points of exact barycenters
S Borgwardt, S Patterson - INFORMS Journal on …, 2024 - pubsonline.informs.org
The computation of exact barycenters for a set of discrete measures is of interest in
applications where sparse solutions are desired and to assess the quality of solutions …
applications where sparse solutions are desired and to assess the quality of solutions …
Latent embedded graphs for image and shape interpolation
In this paper, we introduce latent embedded graphs, a simple approach for shape and
image interpolation using generative neural network models. A latent embedded graph is …
image interpolation using generative neural network models. A latent embedded graph is …
Gaussian Process regression over discrete probability measures: on the non-stationarity relation between Euclidean and Wasserstein Squared Exponential Kernels
Gaussian Process regression is a kernel method successfully adopted in many real-life
applications. Recently, there is a growing interest on extending this method to non …
applications. Recently, there is a growing interest on extending this method to non …