Haodong Duan
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Human-Computer Interaction top 2%
- Control and Systems Engineering
- Topics
- Human Pose and Action Recognition (7 papers)Multimodal Machine Learning Applications (5 papers)Anomaly Detection Techniques and Applications (3 papers)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Proceedings of the 30th ACM International Conference on MultimediaProceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Haodong Duan
13 papers receiving 615 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Computer Vision and Pattern Recognition 532
- Artificial Intelligence 279
- Biomedical Engineering 222
- Human-Computer Interaction 154
- Control and Systems Engineering 26
Countries citing papers authored by Haodong Duan
This map shows the geographic impact of Haodong Duan'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 Haodong Duan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haodong Duan more than expected).
Fields of papers citing papers by Haodong Duan
This network shows the impact of papers produced by Haodong Duan. 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 Haodong Duan. The network helps show where Haodong Duan may publish in the future.
Co-authorship network of co-authors of Haodong Duan
This figure shows the co-authorship network connecting the top 25 collaborators of Haodong Duan. A scholar is included among the top collaborators of Haodong Duan 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 Haodong Duan. Haodong Duan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 13 | |
| 8 | 8 | |
| 9 | 3 | |
| 10 | 0 | |
| 11 | 4 | |
| 12 | 18 | |
| 13 | 26 | |
| 14 | 94 | |
| 15 | 20 | |
| 16 | 13 | |
| 17 | Revisiting Skeleton-based Action Recognitionbreakdown → | 417 |
| 18 | 11 |
About Haodong Duan
Haodong Duan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Science Applications, having authored 18 papers that have together received 629 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (7 papers), Multimodal Machine Learning Applications (5 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Human-Computer Interaction (154 citations), Computer Vision and Pattern Recognition (532 citations) and Artificial Intelligence (279 citations). Haodong Duan has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Dahua Lin, Kai Chen, Bo Dai, Yue Zhao, Kai Chen, Jiaqi Wang, Jiaqi Wang, Bing Su, Anyi Rao and Jintao Lin. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Proceedings of the 30th ACM International Conference on Multimedia and Proceedings of the AAAI Conference on Artificial Intelligence.
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.