Stéphane Lathuilière
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Signal Processing top 10%
- Biomedical Engineering
- Control and Systems Engineering
- Co-authors
- Radu HoraudPablo MesejoXavier Alameda-PinedaNicu SebeElisa RicciEnver SanginetoAliaksandr SiarohinMoin Nabi
- Topics
- Domain Adaptation and Few-Shot Learning (10 papers)Generative Adversarial Networks and Image Synthesis (9 papers)Advanced Image Processing Techniques (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Graphics and Computer-Aided Design
In The Last Decade
Stéphane Lathuilière
30 papers receiving 629 citations
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 369
- Artificial Intelligence 244
- Signal Processing 64
- Biomedical Engineering 48
- Control and Systems Engineering 35
Countries citing papers authored by Stéphane Lathuilière
This map shows the geographic impact of Stéphane Lathuilière'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 Stéphane Lathuilière with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stéphane Lathuilière more than expected).
Fields of papers citing papers by Stéphane Lathuilière
This network shows the impact of papers produced by Stéphane Lathuilière. 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 Stéphane Lathuilière. The network helps show where Stéphane Lathuilière may publish in the future.
Co-authorship network of co-authors of Stéphane Lathuilière
This figure shows the co-authorship network connecting the top 25 collaborators of Stéphane Lathuilière. A scholar is included among the top collaborators of Stéphane Lathuilière 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 Stéphane Lathuilière. Stéphane Lathuilière is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 5 | |
| 3 | 7 | |
| 4 | 6 | |
| 5 | 18 | |
| 6 | 4 | |
| 7 | 8 | |
| 8 | 4 | |
| 9 | 7 | |
| 10 | 8 | |
| 11 | 83 | |
| 12 | 4 | |
| 13 | 1 | |
| 14 | 192 | |
| 15 | 21 | |
| 16 | 59 | |
| 17 | 5 | |
| 18 | Camera Adversarial Transfer for Unsupervised Person Re-Identification. | 3 |
| 19 | 0 | |
| 20 | 35 |
About Stéphane Lathuilière
Stéphane Lathuilière is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 32 papers that have together received 643 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (10 papers), Generative Adversarial Networks and Image Synthesis (9 papers) and Advanced Image Processing Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (369 citations), Artificial Intelligence (244 citations) and Computer Graphics and Computer-Aided Design (21 citations). Stéphane Lathuilière has collaborated with scholars based in France, Italy and China. Frequent co-authors include Radu Horaud, Pablo Mesejo, Xavier Alameda-Pineda, Nicu Sebe, Elisa Ricci, Enver Sangineto, Aliaksandr Siarohin, Moin Nabi, Enrico Fini and Zhun Zhong. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and Neurocomputing.
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.