Limin Wang
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.2%
- Biomedical Engineering top 2%
- Human-Computer Interaction top 0.5%
- Aerospace Engineering top 5%
- Topics
- Human Pose and Action Recognition (64 papers)Multimodal Machine Learning Applications (36 papers)Anomaly Detection Techniques and Applications (34 papers)
- Journals
- Physical Review LettersPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ChinaHong KongSwitzerland
In The Last Decade
Limin Wang
135 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Computer Vision and Pattern Recognition 5.7k
- Artificial Intelligence 2.9k
- Biomedical Engineering 1.2k
- Human-Computer Interaction 626
- Aerospace Engineering 325
Countries citing papers authored by Limin Wang
This map shows the geographic impact of Limin Wang'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 Limin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Limin Wang more than expected).
Fields of papers citing papers by Limin Wang
This network shows the impact of papers produced by Limin Wang. 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 Limin Wang. The network helps show where Limin Wang may publish in the future.
Co-authorship network of co-authors of Limin Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Limin Wang. A scholar is included among the top collaborators of Limin Wang 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 Limin Wang. Limin Wang 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 | 10 | |
| 4 | 2 | |
| 5 | 27 | |
| 6 | 26 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 8 | |
| 10 | 0 | |
| 11 | 44 | |
| 12 | TEA: Temporal Excitation and Aggregation for Action Recognitionbreakdown → | 368 |
| 13 | Image Generation from Freehand Scene Sketches | 1 |
| 14 | V4D: 4D Covolutional Neural Networks for Video-level Representations Learning | 5 |
| 15 | 112 | |
| 16 | Winter wheat stripe rust remote sensing monitoring based on GF-1/WFV data. | 4 |
| 17 | 82 | |
| 18 | 60 | |
| 19 | ON THE GENESIS OF THE YUSHUI POLYMETALLIC DEPOSIT IN MEIXIAN COUNTY, GUANGDONG PROVINCE | 4 |
| 20 | Progressive Image Transmission by Multistage Transform Coefficient Quantization. | 4 |
About Limin Wang
Limin Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 144 papers that have together received 6.8k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (64 papers), Multimodal Machine Learning Applications (36 papers) and Anomaly Detection Techniques and Applications (34 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.7k citations), Human-Computer Interaction (626 citations) and Artificial Intelligence (2.9k citations). Limin Wang has collaborated with scholars based in China, Hong Kong and Switzerland. Frequent co-authors include Yu Qiao, Gangshan Wu, Xiaoou Tang, Luc Van Gool, Yuanjun Xiong, Dahua Lin, Xiaojiang Peng, Yutao Cui, Bin Ji and Zhe Wang. Their work appears in journals such as Physical Review Letters, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine 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.