Fang Wen

248 total papers · 13.6k total citations
124 papers, 7.0k citations indexed

About

Fang Wen is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Fang Wen has authored 124 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Computer Vision and Pattern Recognition, 33 papers in Electrical and Electronic Engineering and 13 papers in Artificial Intelligence. Recurrent topics in Fang Wen's work include Face recognition and analysis (24 papers), Generative Adversarial Networks and Image Synthesis (16 papers) and Energy Harvesting in Wireless Networks (15 papers). Fang Wen is often cited by papers focused on Face recognition and analysis (24 papers), Generative Adversarial Networks and Image Synthesis (16 papers) and Energy Harvesting in Wireless Networks (15 papers). Fang Wen collaborates with scholars based in China, United States and United Kingdom. Fang Wen's co-authors include Jian Sun, Dong Chen, Xudong Cao, Jianmin Bao, Yichen Wei, Dong Chen, Hao Yang, Baining Guo, Gang Hua and Lingzhi Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Signal Processing and Optics Letters.

In The Last Decade

Fang Wen

110 papers receiving 6.8k citations

Hit Papers

Face X-Ray for More Gener... 2013 2026 2017 2021 2020 2013 2013 2017 2022 200 400 600

Author Peers

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

Author Last Decade Papers Cites
Fang Wen 5.4k 1.4k 1.0k 496 460 124 7.0k
Edwin R. Hancock 4.6k 0.8× 2.4k 1.7× 966 1.0× 779 1.6× 525 1.1× 484 7.3k
Bernard Ghanem 7.0k 1.3× 2.9k 2.0× 471 0.5× 1.1k 2.2× 209 0.5× 203 9.4k
Martin D. Levine 3.9k 0.7× 953 0.7× 244 0.2× 377 0.8× 238 0.5× 143 5.7k
Ling‐Yu Duan 6.7k 1.2× 1.9k 1.4× 835 0.8× 154 0.3× 139 0.3× 240 7.7k
Cha Zhang 4.0k 0.7× 1.4k 1.0× 1.5k 1.5× 635 1.3× 476 1.0× 124 6.5k
Robert T. Collins 6.3k 1.2× 1.2k 0.9× 230 0.2× 501 1.0× 260 0.6× 115 8.3k
Amnon Shashua 3.7k 0.7× 1.2k 0.8× 491 0.5× 393 0.8× 280 0.6× 105 5.3k
A. Murat Tekalp 8.6k 1.6× 692 0.5× 2.7k 2.7× 381 0.8× 260 0.6× 396 10.1k
Anastasios Tefas 4.1k 0.8× 2.8k 1.9× 824 0.8× 228 0.5× 131 0.3× 398 6.9k
Alessandro Verri 3.5k 0.6× 1.0k 0.7× 302 0.3× 441 0.9× 192 0.4× 138 6.0k

Countries citing papers authored by Fang Wen

Since Specialization
Citations

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

Fields of papers citing papers by Fang Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Fang Wen. A scholar is included among the top collaborators of Fang 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 Fang Wen. Fang 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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