Shangzhe Wu
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- Computer Graphics and Visualization Techniques 3
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- Advanced Vision and Imaging 10
- Generative Adversarial Networks and Image Synthesis 4
- Image Enhancement Techniques 2
- Computational Mechanics top 5%
- 3D Shape Modeling and Analysis 7
- Geology top 10%
- 3D Surveying and Cultural Heritage 4
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- Robotics and Sensor-Based Localization 4
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- Human Motion and Animation 2
- Co-authors
- Christian RupprechtAndrea VedaldiErnest M. StokelyTomáš JakabDaniele De MartiniPaul NewmanJiajun WuNoah Snavely
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)International Journal of Computer Vision (1 paper)The International Journal of Robotics Research (1 paper)
- Partner nations
- United KingdomUnited StatesHong Kong
In The Last Decade
Shangzhe Wu
17 papers receiving 385 citations
Peers
Comparison fields: 5 of 59
- Computer Graphics and Computer-Aided Design 103
- Computer Vision and Pattern Recognition 326
- Computational Mechanics 174
- Geology 42
- Aerospace Engineering 65
Countries citing papers authored by Shangzhe Wu
This map shows the geographic impact of Shangzhe 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 Shangzhe Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shangzhe Wu more than expected).
Fields of papers citing papers by Shangzhe Wu
This network shows the impact of papers produced by Shangzhe 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 Shangzhe Wu. The network helps show where Shangzhe Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shangzhe 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 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 7 | |
| 6 | 2023 | 12 | |
| 7 | 2023 | 26 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 4 | |
| 10 | 2022 | 20 | |
| 11 | 2021 | 22 | |
| 12 | 2021 | 19 | |
| 13 | 2021 | 3 | |
| 14 | 2021 | 39 | |
| 15 | 2020 | 144 | |
| 16 | End-to-End Deep HDR Imaging with Large Foreground Motions. | 2017 | 5 |
| 17 | Sketch-to-Image Generation Using Deep Contextual Completion. | 2017 | 4 |
| 18 | 1992 | 93 |
About Shangzhe Wu
Shangzhe Wu is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Geology, having authored 18 papers that have together received 411 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (10 papers), 3D Shape Modeling and Analysis (7 papers), Generative Adversarial Networks and Image Synthesis (4 papers), 3D Surveying and Cultural Heritage (4 papers), Robotics and Sensor-Based Localization (4 papers), Computer Graphics and Visualization Techniques (3 papers), Human Motion and Animation (2 papers) and Image Enhancement Techniques (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (103 citations), Computer Vision and Pattern Recognition (326 citations) and Computational Mechanics (174 citations). Shangzhe Wu has collaborated with scholars based in United Kingdom, United States and Hong Kong. Frequent co-authors include Christian Rupprecht, Andrea Vedaldi, Ernest M. Stokely, Tomáš Jakab, Daniele De Martini, Paul Newman, Jiajun Wu, Noah Snavely, Richard Tucker and Ameesh Makadia. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and The International Journal of Robotics Research.
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.