Etienne Pot
Impact in
-
- Computer Graphics and Visualization Techniques
-
- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
Papers in
-
- Advanced Vision and Imaging 3
- Advanced Image and Video Retrieval Techniques 1
- Image Processing and 3D Reconstruction 1
-
- Computer Graphics and Visualization Techniques 1
- Co-authors
- Bruno Maisonnier (1 shared paper)Rodolphe Gélin (1 shared paper)Mehdi S. M. Sajjadi (2 shared papers)Mario Lučić (2 shared papers)Klaus Greff (2 shared papers)Daniel Duckworth (2 shared papers)Andrea Tagliasacchi (1 shared paper)Jakob Uszkoreit (1 shared paper)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2 papers)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Etienne Pot
5 papers receiving 435 citations
Peers
Comparison fields: 5 of 65
- Computer Graphics and Computer-Aided Design 70
- Computer Vision and Pattern Recognition 226
- Software 27
- Computer Science Applications 34
- Social Psychology 77
Countries citing papers authored by Etienne Pot
This map shows the geographic impact of Etienne Pot'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 Etienne Pot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Etienne Pot more than expected).
Fields of papers citing papers by Etienne Pot
This network shows the impact of papers produced by Etienne Pot. 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 Etienne Pot. The network helps show where Etienne Pot may publish in the future.
Co-authors
The 18 scholars most cited alongside Etienne Pot, 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 | 2009 | 193 | |
| 2 | 2022 | 145 | |
| 3 | 2022 | 95 | |
| 4 | 2023 | 13 | |
| 5 | Self-supervisory Signals for Robotic Object Discovery and Detection | 2018 | 1 |
About Etienne Pot
Etienne Pot is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computer Science Applications, Environmental Engineering and Computational Mechanics, having authored 5 papers that have together received 447 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (3 papers), Advanced Image and Video Retrieval Techniques (1 paper), Robotics and Sensor-Based Localization (1 paper), Robotics and Automated Systems (1 paper), Teaching and Learning Programming (1 paper), Computer Graphics and Visualization Techniques (1 paper), Image Processing and 3D Reconstruction (1 paper) and Modular Robots and Swarm Intelligence (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (70 citations), Computer Vision and Pattern Recognition (226 citations), Software (27 citations), Computer Science Applications (34 citations) and Social Psychology (77 citations). Etienne Pot has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Bruno Maisonnier, Rodolphe Gélin, Mehdi S. M. Sajjadi, Mario Lučić, Klaus Greff, Daniel Duckworth, Andrea Tagliasacchi, Jakob Uszkoreit, Urs Bergmann and Thomas Funkhouser. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.