Gengshan Yang
- Computer Vision and Pattern Recognition top 2%
- Computational Mechanics top 10%
- Aerospace Engineering top 10%
- Computer Graphics and Computer-Aided Design top 5%
- Control and Systems Engineering
- Co-authors
- Deva RamananMichael HappoldChao ShenAndrea VedaldiHanbyul JooMinh VoYufei ChenNatalia Neverova
- Topics
- Advanced Vision and Imaging (11 papers)Human Pose and Action Recognition (7 papers)3D Shape Modeling and Analysis (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignComputational Mechanics
- Journals
- IEEE Transactions on Systems Man and Cybernetics SystemsComputers & Security2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesChina
In The Last Decade
Gengshan Yang
16 papers receiving 649 citations
Peers
Comparison fields: 5 of 58
- Computer Vision and Pattern Recognition 555
- Computational Mechanics 132
- Aerospace Engineering 105
- Computer Graphics and Computer-Aided Design 84
- Control and Systems Engineering 55
Countries citing papers authored by Gengshan Yang
This map shows the geographic impact of Gengshan Yang'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 Gengshan Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gengshan Yang more than expected).
Fields of papers citing papers by Gengshan Yang
This network shows the impact of papers produced by Gengshan Yang. 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 Gengshan Yang. The network helps show where Gengshan Yang may publish in the future.
Co-authorship network of co-authors of Gengshan Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Gengshan Yang. A scholar is included among the top collaborators of Gengshan Yang 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 Gengshan Yang. Gengshan Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 10 | |
| 3 | 4 | |
| 4 | 8 | |
| 5 | 7 | |
| 6 | 14 | |
| 7 | 84 | |
| 8 | ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction | 29 |
| 9 | 33 | |
| 10 | 51 | |
| 11 | 52 | |
| 12 | Volumetric Correspondence Networks for Optical Flow | 95 |
| 13 | 9 | |
| 14 | 169 | |
| 15 | 18 | |
| 16 | 28 | |
| 17 | 49 |
About Gengshan Yang
Gengshan Yang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Instrumentation, having authored 17 papers that have together received 660 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Human Pose and Action Recognition (7 papers) and 3D Shape Modeling and Analysis (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (555 citations), Computer Graphics and Computer-Aided Design (84 citations) and Computational Mechanics (132 citations). Gengshan Yang has collaborated with scholars based in United States and China. Frequent co-authors include Deva Ramanan, Michael Happold, Chao Shen, Andrea Vedaldi, Hanbyul Joo, Minh Vo, Yufei Chen, Natalia Neverova, Xiaohong Guan and Varun Jampani. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, Computers & Security and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.