Oier Mees
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Robotic Path Planning Algorithms
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
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- Multimodal Machine Learning Applications 6
- Human Pose and Action Recognition 2
- Advanced Image and Video Retrieval Techniques 2
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- Domain Adaptation and Few-Shot Learning 3
- Topic Modeling 2
- Natural Language Processing Techniques 1
- Co-authors
- Wolfram Burgard (7 shared papers)Andy Zeng (2 shared papers)Chenguang Huang (1 shared paper)Joschka Boedecker (1 shared paper)Gabriel Kalweit (1 shared paper)Thomas Brox (1 shared paper)Maxim Tatarchenko (1 shared paper)Sergey Levine (4 shared papers)
- Journals
- IEEE Robotics and Automation Letters (1 paper)The International Journal of Robotics Research (1 paper)2022 International Conference on Robotics and Automation (ICRA) (1 paper)
- Partner nations
- GermanyUnited States
In The Last Decade
Oier Mees
10 papers receiving 317 citations
Hit Papers
Peers
Comparison fields: 5 of 45
- Computer Vision and Pattern Recognition 188
- Control and Systems Engineering 109
- Artificial Intelligence 146
- Geology 11
- Geography, Planning and Development 10
Countries citing papers authored by Oier Mees
This map shows the geographic impact of Oier Mees'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 Oier Mees with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oier Mees more than expected).
Fields of papers citing papers by Oier Mees
This network shows the impact of papers produced by Oier Mees. 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 Oier Mees. The network helps show where Oier Mees may publish in the future.
Co-authors
The 24 scholars most cited alongside Oier Mees, 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 | Visual Language Maps for Robot Navigation Hit paper breakdown → | 2023 | 160 |
| 2 | 2023 | 47 | |
| 3 | 2022 | 40 | |
| 4 | 2024 | 29 | |
| 5 | 2022 | 25 | |
| 6 | 2017 | 13 | |
| 7 | 2019 | 10 | |
| 8 | 2025 | 6 | |
| 9 | 2025 | 2 | |
| 10 | 2025 | 1 | |
| 11 | 2025 | 0 |
About Oier Mees
Oier Mees is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering and Computational Mechanics, having authored 11 papers that have together received 333 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (6 papers), Domain Adaptation and Few-Shot Learning (3 papers), Human Pose and Action Recognition (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Topic Modeling (2 papers), Natural Language Processing Techniques (1 paper), 3D Shape Modeling and Analysis (1 paper) and Distributed and Parallel Computing Systems (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (188 citations), Control and Systems Engineering (109 citations), Artificial Intelligence (146 citations), Geology (11 citations) and Geography, Planning and Development (10 citations). Oier Mees has collaborated with scholars based in Germany and United States. Frequent co-authors include Wolfram Burgard, Andy Zeng, Chenguang Huang, Joschka Boedecker, Gabriel Kalweit, Thomas Brox, Maxim Tatarchenko, Sergey Levine, Quan Vuong and Homer Walke. Their work appears in journals such as IEEE Robotics and Automation Letters, The International Journal of Robotics Research and 2022 International Conference on Robotics and Automation (ICRA).
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.