Yan Di
Impact in
-
- Human Pose and Action Recognition
- Image and Object Detection Techniques
- Advanced Vision and Imaging
- Advanced Neural Network Applications
-
- Robot Manipulation and Learning
Papers in
-
- Human Pose and Action Recognition 5
- Image Processing and 3D Reconstruction 3
- Advanced Neural Network Applications 2
- Digital Imaging for Blood Diseases 1
-
- Robot Manipulation and Learning 7
- Co-authors
- Fabian Manhardt (10 shared papers)Federico Tombari (9 shared papers)Xiangyang Ji (6 shared papers)Nassir Navab (4 shared papers)Ruida Zhang (5 shared papers)Gu Wang (2 shared papers)Benjamin Busam (3 shared papers)Jason Rambach (3 shared papers)
- Journals
- IEEE Robotics and Automation Letters (2 papers)IEEE Transactions on Instrumentation and Measurement (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- GermanyChinaUnited States
In The Last Decade
Yan Di
12 papers receiving 281 citations
Peers
Comparison fields: 5 of 19
- Computer Vision and Pattern Recognition 212
- Control and Systems Engineering 188
- Human-Computer Interaction 37
- Aerospace Engineering 125
- Geology 20
Countries citing papers authored by Yan Di
This map shows the geographic impact of Yan Di'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 Yan Di with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Di more than expected).
Fields of papers citing papers by Yan Di
This network shows the impact of papers produced by Yan Di. 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 Yan Di. The network helps show where Yan Di may publish in the future.
Co-authors
The 23 scholars most cited alongside Yan Di, 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 | 2021 | 101 | |
| 2 | 2022 | 86 | |
| 3 | 2023 | 22 | |
| 4 | 2022 | 22 | |
| 5 | 2023 | 21 | |
| 6 | 2024 | 9 | |
| 7 | 2023 | 7 | |
| 8 | 2024 | 7 | |
| 9 | 2024 | 4 | |
| 10 | 2023 | 4 | |
| 11 | 2024 | 2 | |
| 12 | 2023 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 |
About Yan Di
Yan Di is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Aerospace Engineering, Computational Mechanics and Biomedical Engineering, having authored 14 papers that have together received 286 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (7 papers), Robot Manipulation and Learning (7 papers), Human Pose and Action Recognition (5 papers), Image Processing and 3D Reconstruction (3 papers), 3D Shape Modeling and Analysis (3 papers), Soft Robotics and Applications (2 papers), Advanced Neural Network Applications (2 papers) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (212 citations), Control and Systems Engineering (188 citations), Human-Computer Interaction (37 citations), Aerospace Engineering (125 citations) and Geology (20 citations). Yan Di has collaborated with scholars based in Germany, China and United States. Frequent co-authors include Fabian Manhardt, Federico Tombari, Xiangyang Ji, Nassir Navab, Ruida Zhang, Gu Wang, Benjamin Busam, Jason Rambach, Dianye Huang and Didier Stricker. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Transactions on Instrumentation and Measurement, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.