Jack M. Wang

1.4k citations
14 papers · 1.0k · h-index 13

Impact in

Papers in

Jack M. Wang

14 papers receiving 983 citations

Peers

Jack M. Wang
Comparison fields: 5 of 65
  • Computer Vision and Pattern Recognition 628
  • Control and Systems Engineering 633
  • Physical Therapy, Sports Therapy and Rehabilitation 55
  • Human-Computer Interaction 74
  • Computer Graphics and Computer-Aided Design 46
Replace Emre Aksan with:
Emre Aksan Switzerland
Timo von Marcard Germany
Manuel Kaufmann Germany
Panna Felsen United States
Srinath Sridhar Germany
Mohammad Shafiei Iran
Sebastian Starke Germany
R. Plankers Switzerland
Štěpán Obdržálek Czechia
Cary B. Phillips United States
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Countries citing papers authored by Jack M. Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jack M. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack M. Wang. 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 Jack M. Wang. The network helps show where Jack M. Wang may publish in the future.

Co-authors

The 12 scholars most cited alongside Jack M. Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jack M. Wang Line = papers co-authored together Jack M. Wang links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2012211
2 2009143
3 2012119
4 2007100
5 201586
6 201086
7 200879
8 201356
9 201246
10 200936
11 201223
12
Segmentation-Based 3D Artistic Rendering
200815
13 201012
14 20102

About Jack M. Wang

Jack M. Wang is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering, Physical Therapy, Sports Therapy and Rehabilitation and Computational Mechanics, having authored 14 papers that have together received 1.0k indexed citations. Recurring topics across this work include Human Motion and Animation (9 papers), Human Pose and Action Recognition (8 papers), Robotic Locomotion and Control (4 papers), Music Technology and Sound Studies (4 papers), Video Analysis and Summarization (3 papers), Balance, Gait, and Falls Prevention (2 papers), Muscle activation and electromyography studies (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (628 citations), Control and Systems Engineering (633 citations), Physical Therapy, Sports Therapy and Rehabilitation (55 citations), Human-Computer Interaction (74 citations) and Computer Graphics and Computer-Aided Design (46 citations). Jack M. Wang has collaborated with scholars based in Canada, United States and Hong Kong. Frequent co-authors include Aaron Hertzmann, David J. Fleet, Vladlen Koltun, Scott L. Delp, Samuel R. Hamner, Sergey Levine, Zoran Popović, Tim W. Dorn, Jennifer L. Hicks and Emanuel Todorov. Their work appears in journals such as ACM Transactions on Graphics, IEEE Transactions on Pattern Analysis and Machine Intelligence, PLoS ONE and The HKU Scholars Hub (University of Hong Kong).

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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