Liang-Yan Gui
Impact in
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- Computer Graphics and Visualization Techniques
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- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
Papers in
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- Advanced Neural Network Applications 4
- Video Surveillance and Tracking Methods 3
- Visual Attention and Saliency Detection 2
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- Domain Adaptation and Few-Shot Learning 3
- Speech and dialogue systems 2
- Co-authors
- Yu-Xiong Wang (10 shared papers)José M. F. Moura (5 shared papers)Alexander G. Schwing (2 shared papers)Sergey Tulyakov (1 shared paper)Hsin-Ying Lee (1 shared paper)Shengcao Cao (1 shared paper)Dhiraj Joshi (1 shared paper)Manuela Veloso (2 shared papers)
- Journals
- IEEE Control Systems (1 paper)NeuroImage (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- United StatesChinaJamaica
In The Last Decade
Liang-Yan Gui
18 papers receiving 386 citations
Liang-Yan Gui's Hit Papers
Peers
Comparison fields: 5 of 68
- Computer Graphics and Computer-Aided Design 63
- Computer Vision and Pattern Recognition 236
- Computational Mathematics 5
- Computational Mechanics 80
- Human-Computer Interaction 21
Countries citing papers authored by Liang-Yan Gui
This map shows the geographic impact of Liang-Yan Gui'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 Liang-Yan Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liang-Yan Gui more than expected).
Fields of papers citing papers by Liang-Yan Gui
This network shows the impact of papers produced by Liang-Yan Gui. 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 Liang-Yan Gui. The network helps show where Liang-Yan Gui may publish in the future.
Co-authors
The 25 scholars most cited alongside Liang-Yan Gui, 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 | SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation Hit paper breakdown → | 2023 | 97 |
| 2 | 2018 | 68 | |
| 3 | 2023 | 60 | |
| 4 | 2023 | 34 | |
| 5 | 2024 | 29 | |
| 6 | 2023 | 28 | |
| 7 | 2015 | 21 | |
| 8 | 2017 | 21 | |
| 9 | 2012 | 10 | |
| 10 | 2016 | 8 | |
| 11 | 2018 | 7 | |
| 12 | 2024 | 3 | |
| 13 | 2023 | 3 | |
| 14 | 2025 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2011 | 1 | |
| 18 | 2022 | 1 | |
| 19 | 2014 | 0 | |
| 20 | 2012 | 0 |
About Liang-Yan Gui
Liang-Yan Gui is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Computational Mechanics and Electrical and Electronic Engineering, having authored 20 papers that have together received 394 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Video Surveillance and Tracking Methods (3 papers), Visual Attention and Saliency Detection (2 papers), Speech and dialogue systems (2 papers), Human Motion and Animation (2 papers), Cooperative Communication and Network Coding (2 papers) and 3D Shape Modeling and Analysis (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (63 citations), Computer Vision and Pattern Recognition (236 citations), Computational Mathematics (5 citations), Computational Mechanics (80 citations) and Human-Computer Interaction (21 citations). Liang-Yan Gui has collaborated with scholars based in United States, China and Jamaica. Frequent co-authors include Yu-Xiong Wang, José M. F. Moura, Alexander G. Schwing, Sergey Tulyakov, Hsin-Ying Lee, Shengcao Cao, Dhiraj Joshi, Manuela Veloso, Kevin Zhang and Xiaodan Liang. Their work appears in journals such as IEEE Control Systems, NeuroImage 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.