Xin Tao
- Computer Vision and Pattern Recognition top 0.5%
- Media Technology top 0.5%
- Public Health, Environmental and Occupational Health top 10%
- Modeling and Simulation top 2%
- Genetics
- Topics
- Advanced Vision and Imaging (15 papers)Advanced Image Processing Techniques (12 papers)Generative Adversarial Networks and Image Synthesis (9 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of HydrologyIEEE Access
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Xin Tao
37 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Computer Vision and Pattern Recognition 1.2k
- Media Technology 498
- Public Health, Environmental and Occupational Health 175
- Modeling and Simulation 174
- Genetics 104
Countries citing papers authored by Xin Tao
This map shows the geographic impact of Xin Tao'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 Xin Tao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Tao more than expected).
Fields of papers citing papers by Xin Tao
This network shows the impact of papers produced by Xin Tao. 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 Xin Tao. The network helps show where Xin Tao may publish in the future.
Co-authorship network of co-authors of Xin Tao
This figure shows the co-authorship network connecting the top 25 collaborators of Xin Tao. A scholar is included among the top collaborators of Xin Tao 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 Xin Tao. Xin Tao 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 | 2 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 8 | |
| 7 | 8 | |
| 8 | 20 | |
| 9 | 10 | |
| 10 | 11 | |
| 11 | 234 | |
| 12 | Image inpainting via generative multi-column convolutional neural networks | 114 |
| 13 | 2 | |
| 14 | 9 | |
| 15 | 15 | |
| 16 | 1 | |
| 17 | The Specialty Visualization Study of Psychometrics in Recent 15 Years: An Analysis Based on Citespace II | 1 |
| 18 | 7 | |
| 19 | 192 | |
| 20 | 5 |
About Xin Tao
Xin Tao is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Media Technology, having authored 40 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (15 papers), Advanced Image Processing Techniques (12 papers) and Generative Adversarial Networks and Image Synthesis (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.2k citations), Media Technology (498 citations) and Modeling and Simulation (174 citations). Xin Tao has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Jiaya Jia, Hongyun Gao, Renjie Liao, Xiaoyong Shen, Jue Wang, Huaiping Zhu, Jinǵan Cui, Ziyang Ma, Ruiyu Li and Xiaojuan Qi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Hydrology and IEEE Access.
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.