In this paper, we explore the topic of graph learning from the perspecti...
In point cloud compression, exploiting temporal redundancy for inter
pre...
Video shared over the internet is commonly referred to as user generated...
Motivated by the success of fractional pixel motion in video coding, we
...
This paper considers the problem of estimating high dimensional Laplacia...
This paper presents a convex-analytic framework to learn sparse graphs f...
We propose an intra frame predictive strategy for compression of 3D poin...
We introduce the Region Adaptive Graph Fourier Transform (RA-GFT) for
co...
In this paper we study covariance estimation with missing data. We consi...
We study covariance matrix estimation for the case of partially observed...
This paper introduces a novel graph signal processing framework for buil...
Learning graphs with topology properties is a non-convex optimization
pr...
Graphs are fundamental mathematical structures used in various fields to...
We introduce the polygon cloud, also known as a polygon set or
soup, a...