Rodrigo Ortiz-Cayon
- Computer Vision and Pattern Recognition top 2%
- Computer Graphics and Computer-Aided Design top 1%
- Computational Mechanics top 5%
- Aerospace Engineering
- Media Technology top 10%
- Co-authors
- Nima Khademi KalantariBen MildenhallRavi RamamoorthiPratul P. SrinivasanRen NgAbhishek KarMatteo MunaroChristian Richardt
- Topics
- Advanced Vision and Imaging (2 papers)Advanced Image Processing Techniques (2 papers)Face recognition and analysis (1 paper)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- ACM Transactions on GraphicsPure (University of Bath)
- Partner nations
- United KingdomUnited States
In The Last Decade
Rodrigo Ortiz-Cayon
3 papers receiving 557 citations
Hit Papers
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 517
- Computer Graphics and Computer-Aided Design 339
- Computational Mechanics 171
- Aerospace Engineering 53
- Media Technology 50
Countries citing papers authored by Rodrigo Ortiz-Cayon
This map shows the geographic impact of Rodrigo Ortiz-Cayon'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 Rodrigo Ortiz-Cayon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rodrigo Ortiz-Cayon more than expected).
Fields of papers citing papers by Rodrigo Ortiz-Cayon
This network shows the impact of papers produced by Rodrigo Ortiz-Cayon. 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 Rodrigo Ortiz-Cayon. The network helps show where Rodrigo Ortiz-Cayon may publish in the future.
Co-authorship network of co-authors of Rodrigo Ortiz-Cayon
This figure shows the co-authorship network connecting the top 25 collaborators of Rodrigo Ortiz-Cayon. A scholar is included among the top collaborators of Rodrigo Ortiz-Cayon 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 Rodrigo Ortiz-Cayon. Rodrigo Ortiz-Cayon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | Local light field fusionbreakdown → | 573 |
About Rodrigo Ortiz-Cayon
Rodrigo Ortiz-Cayon is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 3 papers that have together received 577 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (2 papers), Advanced Image Processing Techniques (2 papers) and Face recognition and analysis (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (339 citations), Computer Vision and Pattern Recognition (517 citations) and Computational Mechanics (171 citations). Rodrigo Ortiz-Cayon has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Nima Khademi Kalantari, Ben Mildenhall, Ravi Ramamoorthi, Pratul P. Srinivasan, Ren Ng, Abhishek Kar, Matteo Munaro, Christian Richardt, Srinivas Rao and Stefan M. Holzer. Their work appears in journals such as ACM Transactions on Graphics and Pure (University of Bath).
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.