Yann Labbé
Impact in
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- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Image and Object Detection Techniques
- Advanced Neural Network Applications
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
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- Advanced Neural Network Applications 3
- Human Pose and Action Recognition 3
- Advanced Vision and Imaging 2
- Robotic Path Planning Algorithms 1
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- Robot Manipulation and Learning 9
- Co-authors
- Mathieu Aubry (6 shared papers)Josef Šivic (6 shared papers)Justin Carpentier (4 shared papers)Tomáš Hodaň (4 shared papers)Bertram Drost (3 shared papers)Carsten Rother (3 shared papers)Jiřı́ Matas (3 shared papers)Eric Brachmann (3 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)IEEE Robotics and Automation Letters (1 paper)Lecture notes in computer science (3 papers)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (2 papers)
- Partner nations
- FranceCzechiaUnited States
In The Last Decade
Yann Labbé
9 papers receiving 235 citations
Peers
Comparison fields: 5 of 27
- Computer Vision and Pattern Recognition 152
- Control and Systems Engineering 144
- Human-Computer Interaction 28
- Aerospace Engineering 114
- Geology 12
Countries citing papers authored by Yann Labbé
This map shows the geographic impact of Yann Labbé'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 Yann Labbé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yann Labbé more than expected).
Fields of papers citing papers by Yann Labbé
This network shows the impact of papers produced by Yann Labbé. 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 Yann Labbé. The network helps show where Yann Labbé may publish in the future.
Co-authors
The 25 scholars most cited alongside Yann Labbé, 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 | 2020 | 56 | |
| 2 | 2023 | 50 | |
| 3 | 2020 | 39 | |
| 4 | 2021 | 31 | |
| 5 | 2024 | 25 | |
| 6 | 2024 | 17 | |
| 7 | 2022 | 13 | |
| 8 | 2020 | 5 | |
| 9 | MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare | 2022 | 1 |
| 10 | 2024 | 0 |
About Yann Labbé
Yann Labbé is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Aerospace Engineering, Geology and Human-Computer Interaction, having authored 10 papers that have together received 237 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (9 papers), Robotics and Sensor-Based Localization (6 papers), Advanced Neural Network Applications (3 papers), Human Pose and Action Recognition (3 papers), Advanced Vision and Imaging (2 papers), 3D Surveying and Cultural Heritage (1 paper), Robotic Path Planning Algorithms (1 paper) and Industrial Vision Systems and Defect Detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (152 citations), Control and Systems Engineering (144 citations), Human-Computer Interaction (28 citations), Aerospace Engineering (114 citations) and Geology (12 citations). Yann Labbé has collaborated with scholars based in France, Czechia and United States. Frequent co-authors include Mathieu Aubry, Josef Šivic, Justin Carpentier, Tomáš Hodaň, Bertram Drost, Carsten Rother, Jiřı́ Matas, Eric Brachmann, Martin Sundermeyer and Gu Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Robotics and Automation Letters, Lecture notes in computer science, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and HAL (Le Centre pour la Communication Scientifique Directe).
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.