Fabián Prada
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Advanced Vision and Imaging 6
- Human Pose and Action Recognition 3
- Generative Adversarial Networks and Image Synthesis 1
- Advanced Image and Video Retrieval Techniques 1
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- 3D Shape Modeling and Analysis 11
- Co-authors
- Chenglei Wu (8 shared papers)Donglai Xiang (5 shared papers)Jessica K. Hodgins (3 shared papers)Misha Kazhdan (4 shared papers)Ming Chuang (3 shared papers)Hugues Hoppe (3 shared papers)Timur Bagautdinov (7 shared papers)Alvaro Collet (2 shared papers)
- Journals
- ACM Transactions on Graphics (7 papers)Computer Graphics Forum (1 paper)Open MIND (1 paper)
- Partner nations
- United StatesIsraelSwitzerland
In The Last Decade
Fabián Prada
14 papers receiving 238 citations
Peers
Comparison fields: 5 of 29
- Computer Graphics and Computer-Aided Design 147
- Computer Vision and Pattern Recognition 179
- Computational Mechanics 172
- Human-Computer Interaction 24
- Control and Systems Engineering 44
Countries citing papers authored by Fabián Prada
This map shows the geographic impact of Fabián Prada'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 Fabián Prada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabián Prada more than expected).
Fields of papers citing papers by Fabián Prada
This network shows the impact of papers produced by Fabián Prada. 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 Fabián Prada. The network helps show where Fabián Prada may publish in the future.
Co-authors
The 25 scholars most cited alongside Fabián Prada, 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 | 2022 | 45 | |
| 2 | 2020 | 41 | |
| 3 | 2021 | 36 | |
| 4 | 2022 | 31 | |
| 5 | 2016 | 26 | |
| 6 | 2017 | 21 | |
| 7 | 2018 | 16 | |
| 8 | 2022 | 10 | |
| 9 | 2023 | 7 | |
| 10 | 2015 | 6 | |
| 11 | 2021 | 4 | |
| 12 | 2024 | 2 | |
| 13 | 2025 | 1 | |
| 14 | 2013 | 1 | |
| 15 | 2025 | 0 |
About Fabián Prada
Fabián Prada is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Control and Systems Engineering and Human-Computer Interaction, having authored 15 papers that have together received 247 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (11 papers), Computer Graphics and Visualization Techniques (11 papers), Advanced Vision and Imaging (6 papers), Human Motion and Animation (3 papers), Human Pose and Action Recognition (3 papers), Virtual Reality Applications and Impacts (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (147 citations), Computer Vision and Pattern Recognition (179 citations), Computational Mechanics (172 citations), Human-Computer Interaction (24 citations) and Control and Systems Engineering (44 citations). Fabián Prada has collaborated with scholars based in United States, Israel and Switzerland. Frequent co-authors include Chenglei Wu, Donglai Xiang, Jessica K. Hodgins, Misha Kazhdan, Ming Chuang, Hugues Hoppe, Timur Bagautdinov, Alvaro Collet, Yaser Sheikh and Shunsuke Saito. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum and Open MIND.
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.