Junbang Liang
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
Papers in
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- 3D Shape Modeling and Analysis 4
- Advanced Numerical Analysis Techniques 2
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- Advanced Vision and Imaging 4
- Co-authors
- Ming C. Lin (10 shared papers)Vladlen Koltun (2 shared papers)Shan Yang (1 shared paper)Song–Hai Zhang (2 shared papers)Miao Wang (2 shared papers)Shao-Ping Lu (1 shared paper)Ralph R. Martin (1 shared paper)Ariel Shamir (1 shared paper)
- Journals
- Corrosion Science (2 papers)Computational Visual Media (2 papers)Applied Surface Science (1 paper)IEEE Transactions on Medical Robotics and Bionics (1 paper)IEEE Transactions on Image Processing (1 paper)
- Partner nations
- United StatesChinaBelgium
In The Last Decade
Junbang Liang
15 papers receiving 204 citations
Peers
Comparison fields: 5 of 48
- Computer Graphics and Computer-Aided Design 48
- Computer Vision and Pattern Recognition 117
- Computational Mechanics 88
- Control and Systems Engineering 35
- Industrial and Manufacturing Engineering 14
Countries citing papers authored by Junbang Liang
This map shows the geographic impact of Junbang Liang'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 Junbang Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junbang Liang more than expected).
Fields of papers citing papers by Junbang Liang
This network shows the impact of papers produced by Junbang Liang. 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 Junbang Liang. The network helps show where Junbang Liang may publish in the future.
Co-authors
The 25 scholars most cited alongside Junbang Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Differentiable Cloth Simulation for Inverse Problems | 2019 | 48 |
| 2 | 2019 | 47 | |
| 3 | 2017 | 45 | |
| 4 | 2016 | 17 | |
| 5 | 2017 | 15 | |
| 6 | 2020 | 10 | |
| 7 | 2021 | 7 | |
| 8 | 2020 | 7 | |
| 9 | 2025 | 3 | |
| 10 | 2018 | 3 | |
| 11 | 2019 | 2 | |
| 12 | 2012 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 1 | |
| 15 | Differentiable Physics Simulation | 2020 | 1 |
| 16 | 2025 | 0 | |
| 17 | 2019 | 0 |
About Junbang Liang
Junbang Liang is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Mechanical Engineering, Materials Chemistry and Computer Networks and Communications, having authored 17 papers that have together received 209 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (4 papers), Advanced Vision and Imaging (4 papers), Intermetallics and Advanced Alloy Properties (3 papers), Advanced Optical Imaging Technologies (2 papers), Energetic Materials and Combustion (2 papers), Advanced Numerical Analysis Techniques (2 papers), Computer Graphics and Visualization Techniques (2 papers) and MXene and MAX Phase Materials (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (48 citations), Computer Vision and Pattern Recognition (117 citations), Computational Mechanics (88 citations), Control and Systems Engineering (35 citations) and Industrial and Manufacturing Engineering (14 citations). Junbang Liang has collaborated with scholars based in United States, China and Belgium. Frequent co-authors include Ming C. Lin, Vladlen Koltun, Shan Yang, Song–Hai Zhang, Miao Wang, Shao-Ping Lu, Ralph R. Martin, Ariel Shamir, Shi‐Min Hu and Xijin Zhang. Their work appears in journals such as Corrosion Science, Computational Visual Media, Applied Surface Science, IEEE Transactions on Medical Robotics and Bionics and IEEE Transactions on Image Processing.
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.