World's Best Scientists 2026 revealed!
Gene Cheung

Gene Cheung

D-Index & Metrics

Computer Science

D-Index
44
Citations
7691
World Ranking
7601
National Ranking
307

Research.com Recognitions

  • 2021 - IEEE Fellow For contributions to graph spectral image processing and interactive video streaming

Overview

Gene Cheung is affiliated with York University in Canada and specializes in research intersecting computer science and engineering. Their scholarly contributions encompass both theoretical and applied aspects within these domains.

Cheung's primary fields of study include:

  • Computer Science
  • Engineering

Within computer science, they concentrate largely on subfields related to:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computational Mechanics
  • Statistical and Nonlinear Physics
  • Radiology, Nuclear Medicine and Imaging

The main topics covered by Cheung's research work are:

  • Advanced Graph Neural Networks
  • Sparse and Compressive Sensing Techniques
  • Complex Network Analysis Techniques
  • Advanced Vision and Imaging
  • Face and Expression Recognition
  • Video Coding and Compression Technologies
  • 3D Shape Modeling and Analysis

Cheung has published extensively, with notable recent papers including:

  • "Sampling Signals on Graphs: From Theory to Applications" (2020) published in IEEE Signal Processing Magazine
  • "Feature Graph Learning for 3D Point Cloud Denoising" (2020) published in IEEE Transactions on Signal Processing
  • "Point Cloud Denoising via Feature Graph Laplacian Regularization" (2020) published in IEEE Transactions on Image Processing
  • "Fast Graph Sampling Set Selection Using Gershgorin Disc Alignment" (2020) published in IEEE Transactions on Signal Processing
  • "Graph Learning Based Head Movement Prediction for Interactive 360 Video Streaming" (2021) published in IEEE Transactions on Image Processing

The frequent publication venues in which Cheung appears are:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE International Conference on Image Processing (ICIP)

Frequent collaborators in Cheung's work include:

  • Chinthaka Dinesh
  • Cheng Yang
  • Fei Chen
  • Xue Zhang
  • Antonio Ortega

Recognition of Cheung's contributions includes being named an IEEE Fellow in 2021 for work relating to graph spectral image processing and interactive video streaming.

Best Publications

  • Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain

    Jiahao Pang;Gene Cheung

  • Multiresolution Graph Fourier Transform for Compression of Piecewise Smooth Images

    Wei Hu;Gene Cheung;Antonio Ortega;Oscar C. Au

  • Bit allocation for joint source/channel coding of scalable video

    G. Cheung;A. Zakhor

  • Graph-Based Blind Image Deblurring From a Single Photograph

    Yuanchao Bai;Gene Cheung;Xianming Liu;Wen Gao

  • 3D Point Cloud Denoising Using Graph Laplacian Regularization of a Low Dimensional Manifold Model

    Jin Zeng;Gene Cheung;Michael Ng;Jiahao Pang

  • Interactive Streaming of Stored Multiview Video Using Redundant Frame Structures

    G Cheung;A Ortega;Ngai-Man Cheung

  • Medium streaming distribution system

    Gene Cheung;Takeshi Yoshimura

  • Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images

    Xianming Liu;Gene Cheung;Xiaolin Wu;Debin Zhao

  • Sampling Signals on Graphs: From Theory to Applications

    Yuichi Tanaka;Yonina C. Eldar;Antonio Ortega;Gene Cheung

  • Graph Spectral Image Processing

    Gene Cheung;Enrico Magli;Yuichi Tanaka;Michael K. Ng

  • Depth map denoising using graph-based transform and group sparsity

    Wei Hu;Xin Li;Gene Cheung;Oscar Au

  • Optimal routing table design for IP address lookups under memory constraints

    G. Cheung;S. McCanne

  • Graph-Based Blind Image Deblurring From a Single Photograph

    Yuanchao Bai;Gene Cheung;Xianming Liu;Wen Gao

  • Method for assigning a streaming media session to a server in fixed and mobile streaming media systems

    John G. Apostolopoulos;Sujoy Basu;Gene Cheung;Rajendra Kumar

  • Feature Graph Learning for 3D Point Cloud Denoising

    Wei Hu;Xiang Gao;Gene Cheung;Zongming Guo

  • On Dependent Bit Allocation for Multiview Image Coding With Depth-Image-Based Rendering

    Gene Cheung;Vladan Velisavljevic;Antonio Ortega

  • Point Cloud Denoising via Feature Graph Laplacian Regularization

    Chinthaka Dinesh;Gene Cheung;Ivan V. Bajic

  • Distribution of packets among a plurality of nodes

    Gene Cheung

  • Multimedia stream pre-fetching and redistribution in servers to accommodate mobile clients

    Gene Cheung;Tina Wong;Susie J. Wee

  • Distributed source coding techniques for interactive multiview video streaming

    Ngai-Man Cheung;Antonio Ortega;Gene Cheung

  • Method for distributing multiple description streams on servers in fixed and mobile streaming media systems

    John G. Apostolopulos;Sujoy Basu;Gene Cheung;Raj Kumar

  • Graph-based Dequantization of Block-Compressed Piecewise Smooth Images

    Wei Hu;Gene Cheung;Masato Kazui

  • Structured Network Coding and Cooperative Wireless Ad-Hoc Peer-to-Peer Repair for WWAN Video Broadcast

    Xin Liu;G. Cheung;Chen-Nee Chuah

  • Random Walk Graph Laplacian based Smoothness Prior for Soft Decoding of JPEG Images

    Xianming Liu;Gene Cheung;Xiaolin Wu;Debin Zhao

Frequent Co-Authors

Antonio Ortega
Antonio Ortega University of Southern California
Yusheng Ji
Yusheng Ji National Institute of Informatics
Pascal Frossard
Pascal Frossard École Polytechnique Fédérale de Lausanne
Zhi Liu
Zhi Liu University of Electro-Communications
Chen-Nee Chuah
Chen-Nee Chuah University of California, Davis
Chia-Wen Lin
Chia-Wen Lin National Tsing Hua University
Ngai-Man Cheung
Ngai-Man Cheung Singapore University of Technology and Design
Dinei Florencio
Dinei Florencio Microsoft (United States)
Wei Hu
Wei Hu Nanjing University
Oscar C. Au
Oscar C. Au Hong Kong University of Science and Technology

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