Chunhua Shen
- Computer Vision and Pattern Recognition top 0.01%
- Artificial Intelligence top 0.05%
- Media Technology top 0.01%
- Aerospace Engineering top 0.1%
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Topics
- Advanced Image and Video Retrieval Techniques (106 papers)Advanced Neural Network Applications (87 papers)Video Surveillance and Tracking Methods (75 papers)
In The Last Decade
Chunhua Shen
346 papers receiving 32.1k citations
Hit Papers
Peers
Comparison fields: 5 of 193
- Computer Vision and Pattern Recognition 25.2k
- Artificial Intelligence 9.6k
- Media Technology 5.4k
- Aerospace Engineering 3.3k
- Radiology, Nuclear Medicine and Imaging 2.0k
Countries citing papers authored by Chunhua Shen
This map shows the geographic impact of Chunhua Shen'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 Chunhua Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chunhua Shen more than expected).
Fields of papers citing papers by Chunhua Shen
This network shows the impact of papers produced by Chunhua Shen. 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 Chunhua Shen. The network helps show where Chunhua Shen may publish in the future.
Co-authorship network of co-authors of Chunhua Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Chunhua Shen. A scholar is included among the top collaborators of Chunhua Shen 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 Chunhua Shen. Chunhua Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 20 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 24 | |
| 7 | 5 | |
| 8 | 19 | |
| 9 | 1 | |
| 10 | End-to-End Video Instance Segmentation with Transformersbreakdown → | 433 |
| 11 | 148 | |
| 12 | 11 | |
| 13 | 47 | |
| 14 | 56 | |
| 15 | SOLOv2: Dynamic and Fast Instance Segmentation | 25 |
| 16 | FCOS: Fully Convolutional One-Stage Object Detectionbreakdown → | 3976 |
| 17 | 70 | |
| 18 | 63 | |
| 19 | 20 | |
| 20 | 84 |
About Chunhua Shen
Chunhua Shen is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 352 papers that have together received 32.9k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (106 papers), Advanced Neural Network Applications (87 papers) and Video Surveillance and Tracking Methods (75 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (25.2k citations), Media Technology (5.4k citations) and Artificial Intelligence (9.6k citations). Chunhua Shen has collaborated with scholars based in Australia, China and Singapore. Frequent co-authors include Anton van den Hengel, Zhi Tian, Guosheng Lin, Hao Chen, Tong He, Ian Reid, Anton Milan, Zifeng Wu, Anthony Dick and Peng Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, New Phytologist and IEEE Transactions on Geoscience and Remote Sensing.
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.