Seokeon Choi
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Aerospace Engineering
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Changick KimTaekyung KimMinki JeongYoungeun KimSumin LeeSeunghyeon KimJonghee KimWonjun Kim
- Topics
- Video Surveillance and Tracking Methods (5 papers)Human Pose and Action Recognition (5 papers)Advanced Image and Video Retrieval Techniques (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Information Forensics and Security2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- South KoreaCanadaUnited Kingdom
In The Last Decade
Seokeon Choi
13 papers receiving 765 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 662
- Artificial Intelligence 258
- Biomedical Engineering 171
- Aerospace Engineering 62
- Radiology, Nuclear Medicine and Imaging 49
Countries citing papers authored by Seokeon Choi
This map shows the geographic impact of Seokeon Choi'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 Seokeon Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seokeon Choi more than expected).
Fields of papers citing papers by Seokeon Choi
This network shows the impact of papers produced by Seokeon Choi. 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 Seokeon Choi. The network helps show where Seokeon Choi may publish in the future.
Co-authorship network of co-authors of Seokeon Choi
This figure shows the co-authorship network connecting the top 25 collaborators of Seokeon Choi. A scholar is included among the top collaborators of Seokeon Choi 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 Seokeon Choi. Seokeon Choi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 38 | |
| 5 | 35 | |
| 6 | 5 | |
| 7 | 111 | |
| 8 | Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identificationbreakdown → | 258 |
| 9 | 6 | |
| 10 | Bilinear Siamese Networks with Background Suppression for Visual Object Tracking. | 2 |
| 11 | 216 | |
| 12 | 56 | |
| 13 | 14 |
About Seokeon Choi
Seokeon Choi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 13 papers that have together received 774 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (5 papers), Human Pose and Action Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (662 citations), Artificial Intelligence (258 citations) and Human-Computer Interaction (31 citations). Seokeon Choi has collaborated with scholars based in South Korea, Canada and United Kingdom. Frequent co-authors include Changick Kim, Taekyung Kim, Minki Jeong, Youngeun Kim, Sumin Lee, Seunghyeon Kim, Jonghee Kim, Wonjun Kim, Sangbum Choi and Seung-Han Yang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Information Forensics and Security and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.