Wayne Wu
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- Generative Adversarial Networks and Image Synthesis 20
- Face recognition and analysis 12
- Human Pose and Action Recognition 11
- Advanced Vision and Imaging 11
- Video Analysis and Summarization 6
- Signal Processing top 2%
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- Computer Graphics and Visualization Techniques 6
- Human-Computer Interaction top 5%
- Artificial Intelligence top 5%
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- 3D Shape Modeling and Analysis 9
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- Human Motion and Animation 7
Wayne Wu
40 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 1.5k
- Signal Processing 352
- Computer Graphics and Computer-Aided Design 83
- Human-Computer Interaction 109
- Artificial Intelligence 314
Countries citing papers authored by Wayne Wu
This map shows the geographic impact of Wayne Wu'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 Wayne Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wayne Wu more than expected).
Fields of papers citing papers by Wayne Wu
This network shows the impact of papers produced by Wayne Wu. 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 Wayne Wu. The network helps show where Wayne Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Wayne Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 19 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 61 | |
| 10 | 2023 | 25 | |
| 11 | 2022 | 8 | |
| 12 | 2022 | 35 | |
| 13 | 2022 | 81 | |
| 14 | 2022 | 71 | |
| 15 | 2022 | 66 | |
| 16 | 2021 | 126 | |
| 17 | 2021 | 19 | |
| 18 | Focal Frequency Loss for Generative Models | 2020 | 8 |
| 19 | DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detectionbreakdown → | 2020 | 334 |
| 20 | 2018 | 8 |
About Wayne Wu
Wayne Wu is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 41 papers that have together received 1.8k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (20 papers), Face recognition and analysis (12 papers), Human Pose and Action Recognition (11 papers), Advanced Vision and Imaging (11 papers), 3D Shape Modeling and Analysis (9 papers), Human Motion and Animation (7 papers), Video Analysis and Summarization (6 papers) and Computer Graphics and Visualization Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Signal Processing (352 citations) and Computer Graphics and Computer-Aided Design (83 citations). Wayne Wu has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Chen Change Loy, Liming Jiang, Chen Qian, Hang Zhou, Li Ren, Ziwei Liu, Bo Dai, Xiaogang Wang, Yasheng Sun and Kaisiyuan Wang. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Circuits and Systems for Video Technology, ACM Transactions on Graphics, Biology and IEEE Transactions on Information Forensics and Security.
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.