271 citations · 1.3k across the 60 of their papers we have counts for
7 papers · 1 filter
Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative GLASSO and Projection
Saghar Bagheri, Gene Cheung, Antonio Ortega +1
Learning a suitable graph is an important precursor to many graph signal processing (GSP) pipelines, such as graph spectral signal compression and denoising. Previous graph learnin…
Unrolling of Deep Graph Total Variation for Image Denoising
Huy Vu, Gene Cheung, Yonina C. Eldar
While deep learning (DL) architectures like convolutional neural networks (CNNs) have enabled effective solutions in image denoising, in general their implementations overly rely o…
Joint Demosaicking / Rectification of Fisheye Camera Images using Multi-color Graph Laplacian Regularization
Fengbo Lan, Cheng Yang, Gene Cheung +1
To compose a 360 image from a rig with multiple fisheye cameras, a conventional processing pipeline first performs demosaicking on each fisheye camera's Bayer-patterned grid, then…
Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment
Cheng Yang, Gene Cheung, Wei Hu
Given a convex and differentiable objective $Q(\M)$ for a real symmetric matrix $\M$ in the positive definite (PD) cone -- used to compute Mahalanobis distances -- we propose a fas…
Sampling Signals on Graphs: From Theory to Applications
Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega +1
The study of sampling signals on graphs, with the goal of building an analog of sampling for standard signals in the time and spatial domains, has attracted considerable attention…
3D Point Cloud Enhancement using Graph-Modelled Multiview Depth Measurements
Xue Zhang, Gene Cheung, Jiahao Pang +1
A 3D point cloud is often synthesized from depth measurements collected by sensors at different viewpoints. The acquired measurements are typically both coarse in precision and cor…
Graph Metric Learning via Gershgorin Disc Alignment
Cheng Yang, Gene Cheung, Wei Hu
We propose a fast general projection-free metric learning framework, where the minimization objective is a convex differentiable f…