Shih-En Wei

16.6k total citations · 1 hit paper
20 papers, 3.5k citations indexed

About

Shih-En Wei is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Shih-En Wei has authored 20 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 5 papers in Electrical and Electronic Engineering and 4 papers in Computer Networks and Communications. Recurrent topics in Shih-En Wei's work include Human Pose and Action Recognition (6 papers), Face recognition and analysis (6 papers) and Advanced Vision and Imaging (5 papers). Shih-En Wei is often cited by papers focused on Human Pose and Action Recognition (6 papers), Face recognition and analysis (6 papers) and Advanced Vision and Imaging (5 papers). Shih-En Wei collaborates with scholars based in United States, Taiwan and Israel. Shih-En Wei's co-authors include Tomas Simon, Yaser Sheikh, Zhe Cao, Jason Saragih, Stephen Lombardi, Hung‐Yun Hsieh, Ye Yuan, Kris Kitani, Shunsuke Saito and Shoou-I Yu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and ACM Transactions on Graphics.

In The Last Decade

Shih-En Wei

19 papers receiving 3.4k citations

Hit Papers

OpenPose: Realtime Multi-Person 2D Pose Estimation Using ... 2019 2026 2021 2023 2019 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shih-En Wei United States 11 2.3k 767 763 522 384 20 3.5k
Zhe Cao China 7 2.0k 0.9× 685 0.9× 760 1.0× 506 1.0× 409 1.1× 23 3.3k
Toby Sharp United Kingdom 16 4.5k 1.9× 1.8k 2.3× 996 1.3× 775 1.5× 794 2.1× 21 5.7k
Manuel J. Marín‐Jiménez Spain 21 2.5k 1.1× 561 0.7× 728 1.0× 405 0.8× 370 1.0× 65 3.5k
Tomas Simon United States 22 4.1k 1.8× 890 1.2× 824 1.1× 601 1.2× 618 1.6× 36 5.5k
Mykhaylo Andriluka Germany 27 5.9k 2.5× 1.1k 1.4× 920 1.2× 1.6k 3.0× 352 0.9× 31 6.5k
Yaser Sheikh United States 38 6.3k 2.7× 1.2k 1.6× 993 1.3× 947 1.8× 908 2.4× 107 8.0k
Sijie Yan China 11 2.6k 1.1× 624 0.8× 1.1k 1.4× 1.2k 2.3× 437 1.1× 18 3.3k
Leonid Pishchulin Germany 14 2.9k 1.3× 772 1.0× 611 0.8× 717 1.4× 239 0.6× 18 3.3k
Ronald Poppe Netherlands 21 2.4k 1.0× 672 0.9× 716 0.9× 962 1.8× 221 0.6× 84 3.3k
Vlad Olaru Romania 7 1.9k 0.8× 370 0.5× 486 0.6× 306 0.6× 411 1.1× 17 2.2k

Countries citing papers authored by Shih-En Wei

Since Specialization
Citations

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

Fields of papers citing papers by Shih-En Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shih-En Wei. 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 Shih-En Wei. The network helps show where Shih-En Wei may publish in the future.

Co-authorship network of co-authors of Shih-En Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Shih-En Wei. A scholar is included among the top collaborators of Shih-En Wei 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 Shih-En Wei. Shih-En Wei 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.
Xu, Weipeng, Alexander Richard, Shih-En Wei, et al.. (2025). Rewind: Real-Time Egocentric Whole-Body Motion Diffusion with Exemplar-Based Identity Conditioning. 7095–7104. 1 indexed citations
3.
Cao, Chen, Tomas Simon, Jin K. Kim, et al.. (2022). Authentic volumetric avatars from a phone scan. ACM Transactions on Graphics. 41(4). 1–19. 74 indexed citations
4.
Jourabloo, Amin, Fernando De la Torre, Jason Saragih, et al.. (2022). Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 20291–20300. 9 indexed citations
5.
Remelli, Edoardo, Timur Bagautdinov, Shunsuke Saito, et al.. (2022). Drivable Volumetric Avatars using Texel-Aligned Features. 1–9. 42 indexed citations
6.
Bi, Sai, Stephen Lombardi, Shunsuke Saito, et al.. (2021). Deep relightable appearance models for animatable faces. ACM Transactions on Graphics. 40(4). 1–15. 1 indexed citations
7.
Bagautdinov, Timur, Chenglei Wu, Tomas Simon, et al.. (2021). Driving-signal aware full-body avatars. ACM Transactions on Graphics. 40(4). 1–17. 3 indexed citations
8.
Bi, Sai, Stephen Lombardi, Shunsuke Saito, et al.. (2021). Deep relightable appearance models for animatable faces. ACM Transactions on Graphics. 40(4). 1–15. 49 indexed citations
9.
Yuan, Ye, Shih-En Wei, Tomas Simon, Kris Kitani, & Jason Saragih. (2021). SimPoE: Simulated Character Control for 3D Human Pose Estimation. 7155–7165. 80 indexed citations
10.
Dong, Xuanyi, Yi Yang, Shih-En Wei, et al.. (2020). Supervision by Registration and Triangulation for Landmark Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(10). 3681–3694. 35 indexed citations
11.
Schwartz, Gabriel, Shih-En Wei, Stephen Lombardi, et al.. (2020). The eyes have it. ACM Transactions on Graphics. 39(4). 38 indexed citations
12.
Cao, Zhe, et al.. (2019). OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(1). 172–186. 3013 indexed citations breakdown →
13.
Wei, Shih-En, Jason Saragih, Tomas Simon, et al.. (2019). VR facial animation via multiview image translation. ACM Transactions on Graphics. 38(4). 1–16. 94 indexed citations
14.
Wei, Shih-En, Nick C. Tang, Yen‐Yu Lin, Ming-Fang Weng, & Hong-Yuan Mark Liao. (2014). Skeleton-augmented Human Action Understanding by Learning with Progressively Refined Data. 7–10. 8 indexed citations
15.
Tang, Nick C., et al.. (2014). Robust Action Recognition via Borrowing Information Across Video Modalities. IEEE Transactions on Image Processing. 24(2). 709–723. 9 indexed citations
16.
Wei, Shih-En, et al.. (2013). Data-centric clustering for data gathering in machine-to-machine wireless networks. 89–94. 16 indexed citations
17.
Hsieh, Hung‐Yun, et al.. (2013). Optimizing Small Cell Deployment in Arbitrary Wireless Networks with Minimum Service Rate Constraints. IEEE Transactions on Mobile Computing. 13(8). 1801–1815. 21 indexed citations
18.
Wei, Shih-En, Hung‐Yun Hsieh, & Hsuan-Jung Su. (2012). Joint optimization of cluster formation and power control for interference-limited machine-to-machine communications. 5512–5518. 20 indexed citations
19.
Wei, Shih-En, Hung‐Yun Hsieh, & Hsuan-Jung Su. (2012). Enabling dense machine-to-machine communications through interference-controlled clustering. 30. 774–779. 8 indexed citations
20.
Wei, Shih-En, et al.. (2012). Formulating and solving the femtocell deployment problem in two-tier heterogeneous networks. 34. 5053–5058. 9 indexed citations

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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