Soshi Shimada
Impact in
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- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Human-Computer Interaction top 10%
- Hand Gesture Recognition Systems
Papers in
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- Human Pose and Action Recognition 7
- Advanced Vision and Imaging 5
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- Human Motion and Animation 5
- Co-authors
- Vladislav Golyanik (9 shared papers)Christian Theobalt (9 shared papers)Weipeng Xu (3 shared papers)Marc Habermann (2 shared papers)Xinyu Yi (1 shared paper)Feng Xu (1 shared paper)Yuxiao Zhou (1 shared paper)Patrick Pérez (3 shared papers)
- Journals
- ACM Transactions on Graphics (4 papers)Journal of Physics Conference Series (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
In The Last Decade
Soshi Shimada
13 papers receiving 346 citations
Peers
Comparison fields: 5 of 50
- Computer Vision and Pattern Recognition 273
- Human-Computer Interaction 51
- Computer Graphics and Computer-Aided Design 24
- Control and Systems Engineering 141
- Physical Therapy, Sports Therapy and Rehabilitation 16
Countries citing papers authored by Soshi Shimada
This map shows the geographic impact of Soshi Shimada'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 Soshi Shimada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soshi Shimada more than expected).
Fields of papers citing papers by Soshi Shimada
This network shows the impact of papers produced by Soshi Shimada. 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 Soshi Shimada. The network helps show where Soshi Shimada may publish in the future.
Co-authors
The 25 scholars most cited alongside Soshi Shimada, 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 | 2022 | 132 | |
| 2 | 2020 | 106 | |
| 3 | 2021 | 60 | |
| 4 | 2019 | 12 | |
| 5 | 2022 | 11 | |
| 6 | 2023 | 9 | |
| 7 | 2002 | 8 | |
| 8 | 2023 | 6 | |
| 9 | 2024 | 5 | |
| 10 | 2021 | 4 | |
| 11 | 2019 | 1 | |
| 12 | 2004 | 1 | |
| 13 | 2002 | 1 | |
| 14 | 2002 | 0 |
About Soshi Shimada
Soshi Shimada is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Human-Computer Interaction, Computational Mechanics and Rehabilitation, having authored 14 papers that have together received 356 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (7 papers), Advanced Vision and Imaging (5 papers), Human Motion and Animation (5 papers), 3D Shape Modeling and Analysis (2 papers), Hand Gesture Recognition Systems (1 paper), Interactive and Immersive Displays (1 paper), Robotics and Sensor-Based Localization (1 paper) and Industrial Vision Systems and Defect Detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (273 citations), Human-Computer Interaction (51 citations), Computer Graphics and Computer-Aided Design (24 citations), Control and Systems Engineering (141 citations) and Physical Therapy, Sports Therapy and Rehabilitation (16 citations). Soshi Shimada has collaborated with scholars based in Germany, Japan and Israel. Frequent co-authors include Vladislav Golyanik, Christian Theobalt, Weipeng Xu, Marc Habermann, Xinyu Yi, Feng Xu, Yuxiao Zhou, Patrick Pérez, Zhi Li and Bernt Schiele. Their work appears in journals such as ACM Transactions on Graphics, Journal of Physics Conference Series and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.