Sébastien Ehrhardt
Impact in
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- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Advanced Vision and Imaging
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- Domain Adaptation and Few-Shot Learning
- Text and Document Classification Technologies
- Machine Learning and Data Classification
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Multimodal Machine Learning Applications 2
- Advanced Vision and Imaging 2
- Advanced Neural Network Applications 2
- Image Processing and 3D Reconstruction 1
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- Domain Adaptation and Few-Shot Learning 2
- Co-authors
- Andrew Zisserman (3 shared papers)Sylvestre-Alvise Rebuffi (2 shared papers)Kai Han (2 shared papers)Andrea Vedaldi (3 shared papers)Olivia Wiles (1 shared paper)Ingmar Posner (1 shared paper)Martin Engelcke (1 shared paper)Áron Monszpart (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Oxford University Research Archive (ORA) (University of Oxford) (2 papers)arXiv (Cornell University) (2 papers)
- Partner nations
- United Kingdom
In The Last Decade
Sébastien Ehrhardt
5 papers receiving 127 citations
Peers
Comparison fields: 5 of 31
- Computer Vision and Pattern Recognition 86
- Artificial Intelligence 73
- Aerospace Engineering 27
- Media Technology 7
- Geology 4
Countries citing papers authored by Sébastien Ehrhardt
This map shows the geographic impact of Sébastien Ehrhardt'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 Sébastien Ehrhardt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sébastien Ehrhardt more than expected).
Fields of papers citing papers by Sébastien Ehrhardt
This network shows the impact of papers produced by Sébastien Ehrhardt. 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 Sébastien Ehrhardt. The network helps show where Sébastien Ehrhardt may publish in the future.
Co-authors
The 10 scholars most cited alongside Sébastien Ehrhardt, 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 | 2021 | 68 | |
| 2 | Co-attention for conditioned image matching | 2021 | 33 |
| 3 | 2020 | 15 | |
| 4 | D2D: Learning to find good correspondences for image matching and manipulation | 2020 | 11 |
| 5 | RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces | 2020 | 3 |
About Sébastien Ehrhardt
Sébastien Ehrhardt is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computational Mechanics and Infectious Diseases, having authored 5 papers that have together received 130 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), COVID-19 diagnosis using AI (2 papers), Multimodal Machine Learning Applications (2 papers), Advanced Vision and Imaging (2 papers), Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), 3D Shape Modeling and Analysis (1 paper) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (86 citations), Artificial Intelligence (73 citations), Aerospace Engineering (27 citations), Media Technology (7 citations) and Geology (4 citations). Sébastien Ehrhardt has collaborated with scholars based in United Kingdom. Frequent co-authors include Andrew Zisserman, Sylvestre-Alvise Rebuffi, Kai Han, Andrea Vedaldi, Olivia Wiles, Ingmar Posner, Martin Engelcke, Áron Monszpart, Oliver Groth and Niloy J. Mitra. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Oxford University Research Archive (ORA) (University of Oxford) 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.