Shaofan Wang
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- Human Pose and Action Recognition 17
- Advanced Vision and Imaging 15
- Multimodal Machine Learning Applications 8
- Advanced Neural Network Applications 7
- Human-Computer Interaction top 10%
- Transportation top 10%
- Transportation Planning and Optimization 8
- Building and Construction top 10%
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- 3D Shape Modeling and Analysis 14
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- Advanced Graph Neural Networks 10
- Domain Adaptation and Few-Shot Learning 8
- Journals
- IEEE Transactions on Multimedia (6 papers)IEEE Transactions on Intelligent Transportation Systems (5 papers)Neurocomputing (4 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Shaofan Wang
103 papers receiving 718 citations
Peers
Comparison fields: 5 of 117
- Computational Mathematics 7
- Computer Vision and Pattern Recognition 234
- Human-Computer Interaction 41
- Transportation 49
- Building and Construction 73
Countries citing papers authored by Shaofan Wang
This map shows the geographic impact of Shaofan 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 Shaofan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaofan Wang more than expected).
Fields of papers citing papers by Shaofan Wang
This network shows the impact of papers produced by Shaofan 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 Shaofan Wang. The network helps show where Shaofan Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shaofan 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 | 2025 | 0 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 2 | |
| 13 | 2023 | 2 | |
| 14 | 2022 | 1 | |
| 15 | 2021 | 13 | |
| 16 | 2021 | 0 | |
| 17 | 2021 | 12 | |
| 18 | 2021 | 1 | |
| 19 | 2018 | 8 | |
| 20 | 2016 | 9 |
About Shaofan Wang
Shaofan Wang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computational Mathematics, Transportation and Human-Computer Interaction, having authored 115 papers that have together received 738 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (17 papers), Advanced Vision and Imaging (15 papers), 3D Shape Modeling and Analysis (14 papers), Advanced Graph Neural Networks (10 papers), Domain Adaptation and Few-Shot Learning (8 papers), Transportation Planning and Optimization (8 papers), Multimodal Machine Learning Applications (8 papers) and Advanced Neural Network Applications (7 papers). The work is most often cited by research in Computational Mathematics (7 citations), Computer Vision and Pattern Recognition (234 citations), Human-Computer Interaction (41 citations), Transportation (49 citations) and Building and Construction (73 citations). Shaofan Wang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Baocai Yin, Dehui Kong, Shi Qiu, Jinghua Li, Yong Zhang, Yongli Hu, Kelvin C. P. Wang, Baocai Yin, Lichun Wang and Yanfeng Sun. Their work appears in journals such as IEEE Transactions on Multimedia, IEEE Transactions on Intelligent Transportation Systems, Neurocomputing, Multimedia Tools and Applications and IEEE Transactions on Big Data.
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.