Gyeongsik Moon
- Computer Vision and Pattern Recognition top 1%
- Human-Computer Interaction top 2%
- Control and Systems Engineering top 5%
- Computational Mechanics top 10%
- Media Technology top 5%
- Co-authors
- Kyoung Mu LeeJu Yong ChangHongsuk ChoiSungyong BaikRadu TimofteSeungjun NahSanghyun SonSeokil Hong
- Topics
- Human Pose and Action Recognition (13 papers)3D Shape Modeling and Analysis (6 papers)Video Surveillance and Tracking Methods (4 papers)
- Journals
- Journal of Navigation2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Open Access System for Information Sharing (Pohang University of Science and Technology)
- Partner nations
- South KoreaUnited StatesSwitzerland
In The Last Decade
Gyeongsik Moon
17 papers receiving 773 citations
Peers
Comparison fields: 5 of 61
- Computer Vision and Pattern Recognition 722
- Human-Computer Interaction 227
- Control and Systems Engineering 173
- Computational Mechanics 126
- Media Technology 103
Countries citing papers authored by Gyeongsik Moon
This map shows the geographic impact of Gyeongsik Moon'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 Gyeongsik Moon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gyeongsik Moon more than expected).
Fields of papers citing papers by Gyeongsik Moon
This network shows the impact of papers produced by Gyeongsik Moon. 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 Gyeongsik Moon. The network helps show where Gyeongsik Moon may publish in the future.
Co-authorship network of co-authors of Gyeongsik Moon
This figure shows the co-authorship network connecting the top 25 collaborators of Gyeongsik Moon. A scholar is included among the top collaborators of Gyeongsik Moon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gyeongsik Moon. Gyeongsik Moon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 8 | |
| 4 | 14 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 48 | |
| 9 | 67 | |
| 10 | 6 | |
| 11 | 64 | |
| 12 | 35 | |
| 13 | 24 | |
| 14 | 278 | |
| 15 | Multi-scale Aggregation R-CNN for 2D Multi-person Pose Estimation | 2 |
| 16 | 226 | |
| 17 | 5 |
About Gyeongsik Moon
Gyeongsik Moon is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Computational Mechanics, having authored 17 papers that have together received 799 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (13 papers), 3D Shape Modeling and Analysis (6 papers) and Video Surveillance and Tracking Methods (4 papers). The work is most often cited by research in Human-Computer Interaction (227 citations), Computer Vision and Pattern Recognition (722 citations) and Media Technology (103 citations). Gyeongsik Moon has collaborated with scholars based in South Korea, United States and Switzerland. Frequent co-authors include Kyoung Mu Lee, Ju Yong Chang, Hongsuk Choi, Sungyong Baik, Radu Timofte, Seungjun Nah, Sanghyun Son, Seokil Hong, Minsu Cho and Jaeha Kim. Their work appears in journals such as Journal of Navigation, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Open Access System for Information Sharing (Pohang University of Science and Technology).
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.