Jun Wang
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Image Retrieval and Classification Techniques
- Advanced Neural Network Applications
Papers in
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- Computer Graphics and Visualization Techniques 47
- Geology 46
- 3D Surveying and Cultural Heritage 46
- Journals
- IEEE Transactions on Instrumentation and Measurement (19 papers)Computer-Aided Design (19 papers)Computer Graphics Forum (10 papers)IEEE Transactions on Visualization and Computer Graphics (8 papers)IEEE Robotics and Automation Letters (8 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Jun Wang
317 papers receiving 7.3k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Computer Graphics and Computer-Aided Design 746
- Computer Vision and Pattern Recognition 4.2k
- Geology 934
- Industrial and Manufacturing Engineering 732
- Computational Mechanics 1.5k
Countries citing papers authored by Jun Wang
This map shows the geographic impact of Jun Wang'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 Jun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wang more than expected).
Fields of papers citing papers by Jun Wang
This network shows the impact of papers produced by Jun Wang. 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 Jun Wang. The network helps show where Jun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wang, 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 | 2025 | 1 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 6 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 2 | |
| 10 | 2023 | 13 | |
| 11 | 2023 | 9 | |
| 12 | 2023 | 5 | |
| 13 | 2022 | 12 | |
| 14 | 2022 | 28 | |
| 15 | 2021 | 0 | |
| 16 | 2021 | 3 | |
| 17 | 2020 | 0 | |
| 18 | 2019 | 1 | |
| 19 | 2017 | 72 | |
| 20 | Review of sediment ecological dredging in urban black-odors river treatment | 2011 | 4 |
About Jun Wang
Jun Wang is a scholar working on Computer Graphics and Computer-Aided Design, Geology, Computer Vision and Pattern Recognition, Computational Mechanics and Industrial and Manufacturing Engineering, having authored 343 papers that have together received 7.5k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (69 papers), Robotics and Sensor-Based Localization (51 papers), Computer Graphics and Visualization Techniques (47 papers), 3D Surveying and Cultural Heritage (46 papers), Advanced Neural Network Applications (32 papers), Advanced Vision and Imaging (31 papers), Advanced Numerical Analysis Techniques (31 papers) and Optical measurement and interference techniques (25 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (746 citations), Computer Vision and Pattern Recognition (4.2k citations), Geology (934 citations), Industrial and Manufacturing Engineering (732 citations) and Computational Mechanics (1.5k citations). Jun Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shih‐Fu Chang, Yu–Gang Jiang, Rongrong Ji, Wei Liu, Qian Xie, Sanjiv Kumar, Mingqiang Wei, Qiaoyun Wu, Zhenghao Yu and Kai Xu. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Computer-Aided Design, Computer Graphics Forum, IEEE Transactions on Visualization and Computer Graphics and IEEE Robotics and Automation Letters.
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.