Thu Nguyen-Phuoc
- Computer Vision and Pattern Recognition top 5%
- Computer Graphics and Computer-Aided Design top 2%
- Computational Mechanics top 10%
- Artificial Intelligence
- Geology
- Co-authors
- Christian RichardtYong‐Liang YangLucas TheisChuan LiLei XiaoFeng LiuZhengqin LiDouglas Lanman
- Topics
- Advanced Vision and Imaging (7 papers)3D Shape Modeling and Analysis (7 papers)Generative Adversarial Networks and Image Synthesis (6 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- ACM Transactions on GraphicsComputer Graphics Forum2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Thu Nguyen-Phuoc
9 papers receiving 348 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 317
- Computer Graphics and Computer-Aided Design 175
- Computational Mechanics 140
- Artificial Intelligence 27
- Geology 18
Countries citing papers authored by Thu Nguyen-Phuoc
This map shows the geographic impact of Thu Nguyen-Phuoc'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 Thu Nguyen-Phuoc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thu Nguyen-Phuoc more than expected).
Fields of papers citing papers by Thu Nguyen-Phuoc
This network shows the impact of papers produced by Thu Nguyen-Phuoc. 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 Thu Nguyen-Phuoc. The network helps show where Thu Nguyen-Phuoc may publish in the future.
Co-authorship network of co-authors of Thu Nguyen-Phuoc
This figure shows the co-authorship network connecting the top 25 collaborators of Thu Nguyen-Phuoc. A scholar is included among the top collaborators of Thu Nguyen-Phuoc 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 Thu Nguyen-Phuoc. Thu Nguyen-Phuoc 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 | 0 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 49 | |
| 9 | 6 | |
| 10 | BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images | 5 |
| 11 | 195 | |
| 12 | 90 |
About Thu Nguyen-Phuoc
Thu Nguyen-Phuoc is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 12 papers that have together received 362 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (7 papers), 3D Shape Modeling and Analysis (7 papers) and Generative Adversarial Networks and Image Synthesis (6 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (175 citations), Computer Vision and Pattern Recognition (317 citations) and Computational Mechanics (140 citations). Thu Nguyen-Phuoc has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Christian Richardt, Yong‐Liang Yang, Lucas Theis, Chuan Li, Chuan Li, Lei Xiao, Feng Liu, Zhengqin Li, Douglas Lanman and Jan Kautz. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.