Shuyang Gu
- Computer Vision and Pattern Recognition top 1%
- Computer Graphics and Computer-Aided Design top 2%
- Artificial Intelligence top 10%
- Computational Mechanics top 10%
- Signal Processing top 10%
- Co-authors
- Fang WenDong ChenJianmin BaoBaining GuoBo ZhangLu YuanDongdong ChenTing Zhang
- Topics
- Generative Adversarial Networks and Image Synthesis (7 papers)Complexity and Algorithms in Graphs (5 papers)Complex Network Analysis Techniques (4 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionMedia Technology
- Journals
- Theoretical Computer ScienceJournal of Parallel and Distributed ComputingJournal of Global Optimization
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Shuyang Gu
22 papers receiving 965 citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 723
- Computer Graphics and Computer-Aided Design 180
- Artificial Intelligence 156
- Computational Mechanics 106
- Signal Processing 62
Countries citing papers authored by Shuyang Gu
This map shows the geographic impact of Shuyang Gu'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 Shuyang Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuyang Gu more than expected).
Fields of papers citing papers by Shuyang Gu
This network shows the impact of papers produced by Shuyang Gu. 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 Shuyang Gu. The network helps show where Shuyang Gu may publish in the future.
Co-authorship network of co-authors of Shuyang Gu
This figure shows the co-authorship network connecting the top 25 collaborators of Shuyang Gu. A scholar is included among the top collaborators of Shuyang Gu 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 Shuyang Gu. Shuyang Gu 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 | 2 | |
| 3 | 0 | |
| 4 | 17 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 28 | |
| 8 | Vector Quantized Diffusion Model for Text-to-Image Synthesisbreakdown → | 355 |
| 9 | 5 | |
| 10 | StyleSwin: Transformer-based GAN for High-resolution Image Generationbreakdown → | 150 |
| 11 | 4 | |
| 12 | 0 | |
| 13 | 57 | |
| 14 | 3 | |
| 15 | 3 | |
| 16 | 4 | |
| 17 | 1 | |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 3 |
About Shuyang Gu
Shuyang Gu is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 26 papers that have together received 984 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (7 papers), Complexity and Algorithms in Graphs (5 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (180 citations), Computer Vision and Pattern Recognition (723 citations) and Media Technology (58 citations). Shuyang Gu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Fang Wen, Dong Chen, Jianmin Bao, Baining Guo, Bo Zhang, Lu Yuan, Dongdong Chen, Ting Zhang, Bowen Zhang and Yong Wang. Their work appears in journals such as Theoretical Computer Science, Journal of Parallel and Distributed Computing and Journal of Global Optimization.
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.