Zimo Liu
Impact in
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- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Face recognition and analysis
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
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- Gait Recognition and Analysis
Papers in
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- Video Surveillance and Tracking Methods 5
- Human Pose and Action Recognition 4
- Advanced Image and Video Retrieval Techniques 1
- Video Analysis and Summarization 1
- Face recognition and analysis 1
- Multimodal Machine Learning Applications 1
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- Gait Recognition and Analysis 2
- Co-authors
- Huchuan Lu (3 shared papers)Jingya Wang (2 shared papers)Shang Gao (1 shared paper)Dong Wang (1 shared paper)Shaogang Gong (1 shared paper)Dacheng Tao (1 shared paper)Huchuan Lu (1 shared paper)Xiang Ruan (1 shared paper)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Queen Mary Research Online (Queen Mary University of London) (1 paper)
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Zimo Liu
6 papers receiving 389 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 364
- Biomedical Engineering 159
- Safety, Risk, Reliability and Quality 22
- Artificial Intelligence 57
- Media Technology 8
Countries citing papers authored by Zimo Liu
This map shows the geographic impact of Zimo Liu'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 Zimo Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zimo Liu more than expected).
Fields of papers citing papers by Zimo Liu
This network shows the impact of papers produced by Zimo Liu. 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 Zimo Liu. The network helps show where Zimo Liu may publish in the future.
Co-authors
The 14 scholars most cited alongside Zimo Liu, 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 | 2020 | 185 | |
| 2 | 2017 | 125 | |
| 3 | 2019 | 63 | |
| 4 | 2019 | 13 | |
| 5 | 2024 | 9 | |
| 6 | 2025 | 2 |
About Zimo Liu
Zimo Liu is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Epidemiology, Transportation and Management Science and Operations Research, having authored 6 papers that have together received 397 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (5 papers), Human Pose and Action Recognition (4 papers), Gait Recognition and Analysis (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Video Analysis and Summarization (1 paper), Face recognition and analysis (1 paper), Multimodal Machine Learning Applications (1 paper) and Data Quality and Management (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (364 citations), Biomedical Engineering (159 citations), Safety, Risk, Reliability and Quality (22 citations), Artificial Intelligence (57 citations) and Media Technology (8 citations). Zimo Liu has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Huchuan Lu, Jingya Wang, Shang Gao, Dong Wang, Shaogang Gong, Dacheng Tao, Huchuan Lu, Xiang Ruan, Ming–Hsuan Yang and Wenming Yang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Proceedings of the AAAI Conference on Artificial Intelligence and Queen Mary Research Online (Queen Mary University of London).
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.