Andrew Tao
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 5%
- Computer Graphics and Computer-Aided Design top 1%
- Media Technology top 2%
- Computational Mechanics top 5%
- Co-authors
- Bryan CatanzaroMing-Yu LiuTing-Chun WangJun-Yan ZhuJan KautzKevin J. ShihFitsum A. RedaKaran Sapra
- Topics
- Generative Adversarial Networks and Image Synthesis (5 papers)Advanced Vision and Imaging (2 papers)Multimodal Machine Learning Applications (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignMedia Technology
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence2021 IEEE/CVF International Conference on Computer Vision (ICCV)arXiv (Cornell University)
- Partner nations
- United StatesUnited KingdomTürkiye
In The Last Decade
Andrew Tao
9 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Computer Vision and Pattern Recognition 2.3k
- Artificial Intelligence 436
- Computer Graphics and Computer-Aided Design 315
- Media Technology 241
- Computational Mechanics 201
Countries citing papers authored by Andrew Tao
This map shows the geographic impact of Andrew Tao'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 Andrew Tao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Tao more than expected).
Fields of papers citing papers by Andrew Tao
This network shows the impact of papers produced by Andrew Tao. 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 Andrew Tao. The network helps show where Andrew Tao may publish in the future.
Co-authorship network of co-authors of Andrew Tao
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Tao. A scholar is included among the top collaborators of Andrew Tao 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 Andrew Tao. Andrew Tao 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 | 60 | |
| 4 | 5 | |
| 5 | 31 | |
| 6 | 1 | |
| 7 | Neural FFTs for Universal Texture Image Synthesis | 7 |
| 8 | Graphical Contrastive Losses for Scene Graph Generation. | 14 |
| 9 | 247 | |
| 10 | High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANsbreakdown → | 2446 |
| 11 | 1 |
About Andrew Tao
Andrew Tao is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Geology, having authored 11 papers that have together received 2.8k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (5 papers), Advanced Vision and Imaging (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.3k citations), Computer Graphics and Computer-Aided Design (315 citations) and Media Technology (241 citations). Andrew Tao has collaborated with scholars based in United States, United Kingdom and Türkiye. Frequent co-authors include Bryan Catanzaro, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu, Jan Kautz, Kevin J. Shih, Fitsum A. Reda, Karan Sapra, Shawn Newsam and Yi Zhu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and arXiv (Cornell University).
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.