Gene Cheung

5.1k citations
259 papers · 3.5k indexed · h-index 31

Gene Cheung

247 papers receiving 3.4k citations

Peers

Gene Cheung
Comparison fields: 5 of 111
  • Computer Vision and Pattern Recognition 2.2k
  • Signal Processing 1.1k
  • Computer Graphics and Computer-Aided Design 191
  • Computer Networks and Communications 640
  • Media Technology 235
Replace M.G. Strintzis with:
M.G. Strintzis Greece
Matthew Brand United States
Anthony Vetro United States
Thrasyvoulos N. Pappas United States
Oscar C. Au Hong Kong
Arun N. Netravali United States
P. J. Narayanan India
Roger Grosse Canada
Zongming Guo China
Xinfeng Zhang China
Gene Cheung relative to M.G. Strintzis Greece M.G. Strintzis's profile →
Citations per field
00.5×4.3×
M.G. Strintzis · 1×
Citations per year

Countries citing papers authored by Gene Cheung

Since Specialization
Citations

This map shows the geographic impact of Gene Cheung's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gene Cheung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gene Cheung more than expected).

Fields of papers citing papers by Gene Cheung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gene Cheung. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gene Cheung. The network helps show where Gene Cheung may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Gene Cheung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gene Cheung Line = papers co-authored together Gene Cheung links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20250
4 20242
5 20232
6 20233
7 20231
8 20231
9
Deep Graph Laplacian Regularization
20182
10 20182
11 201717
12 201714
13 20168
14
Coding and Caching Co-Design for Interactive Multiview Video Streaming
20123
15 201079
16
Bandwidth-Efficient Interactive Multiview Live Video Streaming using Redundant Frame Structures
20095
17
Optimizing SP-frames for error resilience in video streaming
20061
18
On the Complexity of Variants of Cooperative Peer-to-peer Repair for Wireless Broadcasting
20062
19
Reference frame optimization for multipath video streaming using complexity scaling
20043
20 200081

About Gene Cheung

Gene Cheung is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 259 papers that have together received 3.5k indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (95 papers), Advanced Vision and Imaging (83 papers), Image and Video Quality Assessment (55 papers), Advanced Graph Neural Networks (39 papers), Advanced Image Processing Techniques (38 papers), Advanced Data Compression Techniques (34 papers), Cooperative Communication and Network Coding (29 papers) and Image Enhancement Techniques (22 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.2k citations), Signal Processing (1.1k citations) and Computer Graphics and Computer-Aided Design (191 citations). Gene Cheung has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Antonio Ortega, Wei Hu, Jiahao Pang, Oscar C. Au, Cheng Yang, Ivan V. Bajić, Ngai‐Man Cheung, Yusheng Ji, Avideh Zakhor and Chen‐Nee Chuah. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, IEEE Transactions on Signal Processing, IEEE Signal Processing Letters and IEEE Transactions on Circuits and Systems for Video Technology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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