Shilei Wen

85 total papers · 5.5k total citations
31 papers, 1.9k citations indexed

About

Shilei Wen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Shilei Wen has authored 31 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in Shilei Wen's work include Human Pose and Action Recognition (12 papers), Video Surveillance and Tracking Methods (8 papers) and Multimodal Machine Learning Applications (8 papers). Shilei Wen is often cited by papers focused on Human Pose and Action Recognition (12 papers), Video Surveillance and Tracking Methods (8 papers) and Multimodal Machine Learning Applications (8 papers). Shilei Wen collaborates with scholars based in China, United States and Australia. Shilei Wen's co-authors include Errui Ding, Xiao Liu, Tianwei Lin, Xin Li, Dongliang He, Xiang Long, Xiao Tan, Xiao Liu, Wangmeng Zuo and Chuang Gan and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and IEEE Transactions on Multimedia.

In The Last Decade

Shilei Wen

30 papers receiving 1.9k citations

Hit Papers

BMN: Boundary-Matching Ne... 2019 2026 2021 2023 2019 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shilei Wen 1.7k 820 130 102 87 31 1.9k
Zequn Jie 1.6k 0.9× 552 0.7× 131 1.0× 107 1.0× 50 0.6× 47 2.0k
Shoumeng Yan 1.2k 0.7× 898 1.1× 49 0.4× 94 0.9× 91 1.0× 30 1.8k
Jianfeng Wang 1.8k 1.1× 752 0.9× 174 1.3× 135 1.3× 103 1.2× 62 2.6k
Alina Kuznetsova 1.3k 0.8× 709 0.9× 81 0.6× 91 0.9× 59 0.7× 12 1.8k
Quanfu Fan 1.3k 0.8× 578 0.7× 150 1.2× 129 1.3× 139 1.6× 48 2.0k
Yi Zhu 1.3k 0.8× 784 1.0× 147 1.1× 135 1.3× 93 1.1× 52 2.0k
Ruonan Li 1.1k 0.6× 1.2k 1.4× 141 1.1× 37 0.4× 109 1.3× 48 1.9k
Jérôme Berclaz 1.6k 0.9× 522 0.6× 131 1.0× 263 2.6× 84 1.0× 15 1.8k
Suha Kwak 1.8k 1.1× 957 1.2× 115 0.9× 131 1.3× 46 0.5× 52 2.2k
Erjin Zhou 1.9k 1.1× 681 0.8× 248 1.9× 83 0.8× 143 1.6× 15 2.3k

Countries citing papers authored by Shilei Wen

Since Specialization
Citations

This map shows the geographic impact of Shilei Wen'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 Shilei Wen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shilei Wen more than expected).

Fields of papers citing papers by Shilei Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shilei Wen. 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 Shilei Wen. The network helps show where Shilei Wen may publish in the future.

Co-authorship network of co-authors of Shilei Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Shilei Wen. A scholar is included among the top collaborators of Shilei Wen 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 Shilei Wen. Shilei Wen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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