Jun-Cheng Chen

4.8k total citations · 1 hit paper
117 papers, 2.5k citations indexed

About

Jun-Cheng Chen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Jun-Cheng Chen has authored 117 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Computer Vision and Pattern Recognition, 28 papers in Signal Processing and 22 papers in Artificial Intelligence. Recurrent topics in Jun-Cheng Chen's work include Face recognition and analysis (34 papers), Face and Expression Recognition (22 papers) and Biometric Identification and Security (22 papers). Jun-Cheng Chen is often cited by papers focused on Face recognition and analysis (34 papers), Face and Expression Recognition (22 papers) and Biometric Identification and Security (22 papers). Jun-Cheng Chen collaborates with scholars based in Taiwan, United States and China. Jun-Cheng Chen's co-authors include Rama Chellappa, Vishal M. Patel, Carlos D. Castillo, Rajeev Ranjan, David W. Jacobs, Soumyadip Sengupta, Ja‐Ling Wu, Swami Sankaranarayanan, Jingxiao Zheng and Amit Kumar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and The Astrophysical Journal.

In The Last Decade

Jun-Cheng Chen

96 papers receiving 2.4k citations

Hit Papers

Frontal to profile face verification in the wild 2016 2026 2019 2022 2016 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Frontal to profile face verification in the wild
    2016 471 citations Jun-Cheng Chen, Carlos D. Castillo et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jun-Cheng Chen Taiwan 27 1.8k 718 410 200 95 117 2.5k
Jane Bromley United States 11 795 0.4× 210 0.3× 740 1.8× 126 0.6× 147 1.5× 20 1.8k
S. Ramakrishnan United States 22 620 0.3× 338 0.5× 541 1.3× 226 1.1× 63 0.7× 199 2.0k
Fu Jie Huang China 12 1.5k 0.8× 336 0.5× 1.1k 2.7× 160 0.8× 199 2.1× 21 2.6k
Pascal Lamblin Canada 7 742 0.4× 282 0.4× 831 2.0× 125 0.6× 100 1.1× 9 1.9k
Christophe García France 20 1.4k 0.8× 234 0.3× 304 0.7× 41 0.2× 251 2.6× 83 1.9k
Alexander Waibel United States 21 852 0.5× 1.4k 1.9× 2.2k 5.4× 159 0.8× 112 1.2× 95 3.3k
Genevieve Orr United States 8 550 0.3× 185 0.3× 777 1.9× 93 0.5× 83 0.9× 26 1.7k
Zhifeng Li China 26 2.1k 1.2× 946 1.3× 845 2.1× 39 0.2× 113 1.2× 94 2.9k
Özgür Çetin United States 12 549 0.3× 780 1.1× 919 2.2× 120 0.6× 70 0.7× 27 2.0k
Alexander Graves United States 5 806 0.4× 215 0.3× 801 2.0× 75 0.4× 174 1.8× 9 1.8k

Countries citing papers authored by Jun-Cheng Chen

Since Specialization
Citations

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

Fields of papers citing papers by Jun-Cheng Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun-Cheng Chen. 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 Jun-Cheng Chen. The network helps show where Jun-Cheng Chen may publish in the future.

Co-authorship network of co-authors of Jun-Cheng Chen

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

All Works

20 of 20 papers shown
1.
Chen, Jun-Cheng, et al.. (2024). MeDM: Mediating Image Diffusion Models for Video-to-Video Translation with Temporal Correspondence Guidance. Proceedings of the AAAI Conference on Artificial Intelligence. 38(2). 1353–1361. 4 indexed citations
2.
Huang, Po‐Han, et al.. (2023). DEFAEK: Domain Effective Fast Adaptive Network for Face Anti-Spoofing. Neural Networks. 161. 83–91. 3 indexed citations
3.
Chen, Jun-Cheng, et al.. (2023). Towards Adversarial Robustness for Multi-Mode Data through Metric Learning. Sensors. 23(13). 6173–6173. 1 indexed citations
4.
Chen, Jun-Cheng, et al.. (2022). A Comparative Study of Cross-Model Universal Adversarial Perturbation for Face Forgery. 1–5. 2 indexed citations
5.
Yao, Yi, et al.. (2022). Lightweight Deep Learning: An Overview. IEEE Consumer Electronics Magazine. 13(4). 51–64. 81 indexed citations
6.
Chen, Jun-Cheng, et al.. (2021). Lightweight Face Anti-Spoofing Network for Telehealth Applications. IEEE Journal of Biomedical and Health Informatics. 26(5). 1987–1996. 16 indexed citations
7.
Chen, Jun-Cheng, et al.. (2021). Social Media Popularity Prediction Based on Multi-Modal Self-Attention Mechanisms. IEEE Access. 10. 4448–4455. 8 indexed citations
8.
Zheng, Jingxiao, Rajeev Ranjan, Ching‐Hui Chen, et al.. (2020). An Automatic System for Unconstrained Video-Based Face Recognition. IEEE Transactions on Biometrics Behavior and Identity Science. 2(3). 194–209. 31 indexed citations
9.
Ranjan, Rajeev, Ankan Bansal, Jingxiao Zheng, et al.. (2019). A Fast and Accurate System for Face Detection, Identification, and Verification. IEEE Transactions on Biometrics Behavior and Identity Science. 1(2). 82–96. 117 indexed citations
10.
Zhang, Kaicheng, Xiaofeng Wang, Jujia Zhang, et al.. (2019). OPTICAL OBSERVATIONS OF THE TYPE IA SUPERNOVA SN 2011fe IN M101 FOR NEARLY 500 DAYS. OakTrust (Texas A&M University Libraries). 28 indexed citations
11.
Ranjan, Rajeev, Swami Sankaranarayanan, Ankan Bansal, et al.. (2018). Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans. IEEE Signal Processing Magazine. 35(1). 66–83. 128 indexed citations
12.
Chen, Jun-Cheng, et al.. (2016). [Development of a Questionnaire Measuring Sexual Mental Health of Tibetan University Students].. PubMed. 47(3). 382–8. 1 indexed citations
13.
Peng, Wei, Jun-Cheng Chen, Shilong Yang, et al.. (2016). A novel method for the discrimination of Hawthorn and its processed products using an intelligent sensory system and artificial neural networks. Food Science and Biotechnology. 25(6). 1545–1550. 13 indexed citations
14.
Chen, Jun-Cheng, et al.. (2016). Development of precision angle measurement system. 1–5. 4 indexed citations
15.
Zhou, Li, Xiaofeng Wang, Jun-Cheng Chen, et al.. (2013). Supernova 2013N = Psn J11500413+2116460. 3394. 1.
16.
Zhang, Tianmeng, Xiaofeng Wang, Li Zhou, et al.. (2013). Supernova 2013be in IC 3573 = Psn J12362767+1145281. 3470. 1.
17.
Zhang, Tianmeng, Li Zhou, Xiaofeng Wang, et al.. (2013). Supernova 2013ar = Psn J08374502+4928322. 3446. 1. 1 indexed citations
18.
Zhang, Kaicheng, Li Zhou, Xiaofeng Wang, et al.. (2013). Supernova 2013bf = Psn J08583607+5419257. 3471. 1.
19.
Zhou, Li, Xiaofeng Wang, Kaicheng Zhang, et al.. (2013). Supernova 2013cv = Psn J16224316+1857356. 3543. 1.
20.
Zhang, Tianmeng, Jun-Cheng Chen, Xiaofeng Wang, et al.. (2012). Supernova 2012ih in Pgc 19908 = Psn J06564291+4854103. 3366. 1.

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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