Fabrice Rousselle
- Computer Vision and Pattern Recognition top 1%
- Computer Graphics and Computer-Aided Design top 0.5%
- Computational Mechanics top 5%
- Media Technology top 5%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Matthias ZwickerJan NovákClaude KnausThijs VogelsBrian McWilliamsMark MeyerPradeep SenWojciech Jarosz
- Topics
- Computer Graphics and Visualization Techniques (20 papers)Advanced Vision and Imaging (15 papers)Image and Signal Denoising Methods (10 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionMedia Technology
- Partner nations
- SwitzerlandUnited StatesUnited Kingdom
In The Last Decade
Fabrice Rousselle
28 papers receiving 960 citations
Peers
Comparison fields: 5 of 48
- Computer Vision and Pattern Recognition 913
- Computer Graphics and Computer-Aided Design 599
- Computational Mechanics 193
- Media Technology 82
- Radiology, Nuclear Medicine and Imaging 43
Countries citing papers authored by Fabrice Rousselle
This map shows the geographic impact of Fabrice Rousselle'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 Fabrice Rousselle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrice Rousselle more than expected).
Fields of papers citing papers by Fabrice Rousselle
This network shows the impact of papers produced by Fabrice Rousselle. 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 Fabrice Rousselle. The network helps show where Fabrice Rousselle may publish in the future.
Co-authorship network of co-authors of Fabrice Rousselle
This figure shows the co-authorship network connecting the top 25 collaborators of Fabrice Rousselle. A scholar is included among the top collaborators of Fabrice Rousselle 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 Fabrice Rousselle. Fabrice Rousselle 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 | 9 | |
| 3 | 16 | |
| 4 | 3 | |
| 5 | 22 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 19 | |
| 9 | 9 | |
| 10 | 119 | |
| 11 | 200 | |
| 12 | 38 | |
| 13 | 105 | |
| 14 | 21 | |
| 15 | 72 | |
| 16 | 3 | |
| 17 | 60 | |
| 18 | 48 | |
| 19 | 16 | |
| 20 | Efficient Product Importance Sampling using Hierarchical Thresholding | 1 |
About Fabrice Rousselle
Fabrice Rousselle is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 29 papers that have together received 1.0k indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (20 papers), Advanced Vision and Imaging (15 papers) and Image and Signal Denoising Methods (10 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (599 citations), Computer Vision and Pattern Recognition (913 citations) and Media Technology (82 citations). Fabrice Rousselle has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Matthias Zwicker, Jan Novák, Claude Knaus, Thijs Vogels, Brian McWilliams, Mark Meyer, Pradeep Sen, Wojciech Jarosz, David A. Adler and Tony DeRose. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum and The Visual Computer.
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.