271 citations · 1.3k across the 60 of their papers we have counts for
12 papers · 1 filter
3D Point Cloud Denoising via Bipartite Graph Approximation and Reweighted Graph Laplacian
Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic
Point cloud is a collection of 3D coordinates that are discrete geometric samples of an object's 2D surfaces. Imperfection in the acquisition process means that point clouds are of…
Low-complexity Graph Sampling with Noise and Signal Reconstruction via Neumann Series
Fen Wang, Gene Cheung, Yongchao Wang
Graph sampling addresses the problem of selecting a node subset in a graph to collect samples, so that a K-bandlimited signal can be reconstructed in high fidelity. Assuming an ind…
Reconstruction-Cognizant Graph Sampling using Gershgorin Disc Alignment
Yuanchao Bai, Gene Cheung, Fen Wang +2
Graph sampling with noise is a fundamental problem in graph signal processing (GSP). Previous works assume an unbiased least square (LS) signal reconstruction scheme and select sam…
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination
Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su +1
Despite generative adversarial networks (GANs) can hallucinate photo-realistic high-resolution (HR) faces from low-resolution (LR) faces, they cannot guarantee preserving the ident…
Deep Graph Laplacian Regularization for Robust Denoising of Real Images
Jin Zeng, Jiahao Pang, Wenxiu Sun +1
Recent developments in deep learning have revolutionized the paradigm of image restoration. However, its applications on real image denoising are still limited, due to its sensitiv…
Fast 3D Point Cloud Denoising via Bipartite Graph Approximation & Total Variation
Chinthaka Dinesh, Gene Cheung, Ivan V. Bajic +1
Acquired 3D point cloud data, whether from active sensors directly or from stereo-matching algorithms indirectly, typically contain non-negligible noise. To address the point cloud…
Adaptive Non-Rigid Inpainting of 3D Point Cloud Geometry
Chinthaka Dinesh, Ivan V. Bajic, Gene Cheung
In this letter, we introduce several algorithms for geometry inpainting of 3D point clouds with large holes. The algorithms are examplar-based: hole filling is performed iterativel…
3D Point Cloud Denoising using Graph Laplacian Regularization of a Low Dimensional Manifold Model
Jin Zeng, Gene Cheung, Michael Ng +2
3D point cloud - a new signal representation of volumetric objects - is a discrete collection of triples marking exterior object surface locations in 3D space. Conventional imperfe…
A-Optimal Sampling and Robust Reconstruction for Graph Signals via Truncated Neumann Series
Fen Wang, Yongchao Wang, Gene Cheung
Graph signal processing (GSP) studies signals that live on irregular data kernels described by graphs. One fundamental problem in GSP is sampling---from which subset of graph nodes…
Graph-Based Blind Image Deblurring From a Single Photograph
Yuanchao Bai, Gene Cheung, Xianming Liu +1
Blind image deblurring, i.e., deblurring without knowledge of the blur kernel, is a highly ill-posed problem. The problem can be solved in two parts: i) estimate a blur kernel from…
Non-Local Graph-Based Prediction For Reversible Data Hiding In Images
Qi Chang, Gene Cheung, Yao Zhao +2
Reversible data hiding (RDH) is desirable in applications where both the hidden message and the cover medium need to be recovered without loss. Among many RDH approaches is predict…
Graph Spectral Image Processing
Gene Cheung, Enrico Magli, Yuichi Tanaka +1
Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wi…