Weixin Li
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 0.5%
- Computer Networks and Communications top 1%
- Biomedical Engineering top 10%
- Epidemiology
- Co-authors
- Nuno VasconcelosVijay MahadevanYingwei LiQian YuAjay DivakaranHarpreet SawhneyLiqiang NieLinmei Hu
- Topics
- Human Pose and Action Recognition (7 papers)Anomaly Detection Techniques and Applications (6 papers)Video Surveillance and Tracking Methods (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Networks and Communications
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionNeural Information Processing Systems
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Weixin Li
11 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 1.8k
- Computer Vision and Pattern Recognition 1.3k
- Computer Networks and Communications 868
- Biomedical Engineering 401
- Epidemiology 186
Countries citing papers authored by Weixin Li
This map shows the geographic impact of Weixin Li'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 Weixin Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weixin Li more than expected).
Fields of papers citing papers by Weixin Li
This network shows the impact of papers produced by Weixin Li. 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 Weixin Li. The network helps show where Weixin Li may publish in the future.
Co-authorship network of co-authors of Weixin Li
This figure shows the co-authorship network connecting the top 25 collaborators of Weixin Li. A scholar is included among the top collaborators of Weixin Li 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 Weixin Li. Weixin Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 8 | |
| 5 | 63 | |
| 6 | 45 | |
| 7 | Anomaly Detection and Localization in Crowded Scenesbreakdown → | 732 |
| 8 | 26 | |
| 9 | 35 | |
| 10 | Recognizing Activities by Attribute Dynamics | 17 |
| 11 | Anomaly detection in crowded scenesbreakdown → | 1051 |
About Weixin Li
Weixin Li is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 11 papers that have together received 2.0k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (7 papers), Anomaly Detection Techniques and Applications (6 papers) and Video Surveillance and Tracking Methods (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Artificial Intelligence (1.8k citations) and Computer Networks and Communications (868 citations). Weixin Li has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Nuno Vasconcelos, Vijay Mahadevan, Yingwei Li, Qian Yu, Ajay Divakaran, Harpreet Sawhney, Liqiang Nie, Linmei Hu, Ziwei Chen and Yingxia Shao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Neural Information Processing Systems.
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.