Guansong Lu
Impact in
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Generative Adversarial Networks and Image Synthesis
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Advanced Image Processing Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 5
- Multimodal Machine Learning Applications 3
- Advanced Neural Network Applications 2
- Advanced Vision and Imaging 1
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- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- Hao-Shu Fang (1 shared paper)Yu‐Wing Tai (1 shared paper)Jianwen Xie (1 shared paper)Cewu Lu (1 shared paper)Xiaolin Fang (1 shared paper)Kan Ren (1 shared paper)Zhiming Zhou (1 shared paper)Xiaodan Liang (5 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (1 paper)Duo Research Archive (University of Oslo) (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
- Partner nations
- ChinaSwedenUnited Arab Emirates
In The Last Decade
Guansong Lu
7 papers receiving 135 citations
Peers
Comparison fields: 5 of 40
- Computer Vision and Pattern Recognition 113
- Computational Mathematics 1
- Computer Graphics and Computer-Aided Design 5
- Artificial Intelligence 40
- Human-Computer Interaction 6
Countries citing papers authored by Guansong Lu
This map shows the geographic impact of Guansong Lu'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 Guansong Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guansong Lu more than expected).
Fields of papers citing papers by Guansong Lu
This network shows the impact of papers produced by Guansong Lu. 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 Guansong Lu. The network helps show where Guansong Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Guansong Lu, 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 | 2018 | 85 | |
| 2 | 2019 | 17 | |
| 3 | 2022 | 9 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 7 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 5 | |
| 8 | 2025 | 0 | |
| 9 | 2025 | 0 |
About Guansong Lu
Guansong Lu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Museology and Media Technology, having authored 9 papers that have together received 136 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (5 papers), Multimodal Machine Learning Applications (3 papers), 3D Shape Modeling and Analysis (2 papers), Advanced Neural Network Applications (2 papers), 3D Surveying and Cultural Heritage (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Advanced Vision and Imaging (1 paper) and Fashion and Cultural Textiles (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (113 citations), Computational Mathematics (1 citation), Computer Graphics and Computer-Aided Design (5 citations), Artificial Intelligence (40 citations) and Human-Computer Interaction (6 citations). Guansong Lu has collaborated with scholars based in China, Sweden and United Arab Emirates. Frequent co-authors include Hao-Shu Fang, Yu‐Wing Tai, Jianwen Xie, Cewu Lu, Xiaolin Fang, Kan Ren, Zhiming Zhou, Xiaodan Liang, Hang Xu and Yong Yu. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Duo Research Archive (University of Oslo), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.