Ximeng Sun
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Software top 10%
- Computer Networks and Communications
- Information Systems
- Co-authors
- Kate SaenkoRameswar PandaRogério FerisAude OlivaChun-Fu Richard ChenHans VangheluweJörg KienzleSadaf Mustafiz
- Topics
- Human Pose and Action Recognition (5 papers)Advanced Vision and Imaging (4 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceSoftware & Systems Modeling2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Ximeng Sun
11 papers receiving 136 citations
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 84
- Artificial Intelligence 55
- Software 22
- Computer Networks and Communications 16
- Information Systems 11
Countries citing papers authored by Ximeng Sun
This map shows the geographic impact of Ximeng Sun'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 Ximeng Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ximeng Sun more than expected).
Fields of papers citing papers by Ximeng Sun
This network shows the impact of papers produced by Ximeng Sun. 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 Ximeng Sun. The network helps show where Ximeng Sun may publish in the future.
Co-authorship network of co-authors of Ximeng Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Ximeng Sun. A scholar is included among the top collaborators of Ximeng Sun 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 Ximeng Sun. Ximeng Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 8 | |
| 4 | 31 | |
| 5 | 30 | |
| 6 | 9 | |
| 7 | AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning | 9 |
| 8 | 16 | |
| 9 | A Two-Stream Variational Adversarial Network for Video Generation. | 4 |
| 10 | 23 | |
| 11 | 6 |
About Ximeng Sun
Ximeng Sun is a scholar working on Software, Computer Vision and Pattern Recognition and Information Systems and Management, having authored 11 papers that have together received 142 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (5 papers), Advanced Vision and Imaging (4 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Software (22 citations), Computer Vision and Pattern Recognition (84 citations) and Artificial Intelligence (55 citations). Ximeng Sun has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Kate Saenko, Rameswar Panda, Rogério Feris, Aude Oliva, Chun-Fu Richard Chen, Hans Vangheluwe, Jörg Kienzle, Sadaf Mustafiz, Quanfu Fan and Huijuan Xu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Software & Systems Modeling and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.