Oier Mees

863 total citations · 1 hit paper
11 papers, 333 citations indexed

About

Oier Mees is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Oier Mees has authored 11 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Oier Mees's work include Multimodal Machine Learning Applications (6 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Topic Modeling (2 papers). Oier Mees is often cited by papers focused on Multimodal Machine Learning Applications (6 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Topic Modeling (2 papers). Oier Mees collaborates with scholars based in Germany and United States. Oier Mees's co-authors include Wolfram Burgard, Chenguang Huang, Andy Zeng, Joschka Boedecker, Gabriel Kalweit, Maxim Tatarchenko, Sergey Levine, Thomas Brox, Dorsa Sadigh and Quan Vuong and has published in prestigious journals such as The International Journal of Robotics Research, IEEE Robotics and Automation Letters and 2022 International Conference on Robotics and Automation (ICRA).

In The Last Decade

Oier Mees

10 papers receiving 317 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Visual Language Maps for Robot Navigation

2023 160 citations Chenguang Huang, Oier Mees et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Oier Mees Germany	7	188	146	109	44	18	11	333
Linxi Fan United States	7	124 0.7×	103 0.7×	73 0.7×	38 0.9×	8 0.4×	12	239
Yusuke Yoshiyasu Japan	10	177 0.9×	52 0.4×	57 0.5×	67 1.5×	60 3.3×	37	249
Tingwu Wang Canada	4	200 1.1×	150 1.0×	105 1.0×	15 0.3×	20 1.1×	6	328
Nathan Hughes United States	6	147 0.8×	45 0.3×	25 0.2×	96 2.2×	21 1.2×	10	217
Manuel Wüthrich Germany	9	120 0.6×	101 0.7×	149 1.4×	60 1.4×	8 0.4×	17	269
Stephen James United Kingdom	9	188 1.0×	133 0.9×	210 1.9×	95 2.2×	9 0.5×	13	358
Christopher Xie United States	6	147 0.8×	48 0.3×	60 0.6×	47 1.1×	16 0.9×	7	187
Bokui Shen United States	5	121 0.6×	36 0.2×	48 0.4×	44 1.0×	17 0.9×	12	170
Ferenc Bálint-Benczédi Germany	10	118 0.6×	103 0.7×	103 0.9×	55 1.3×	3 0.2×	21	246

Countries citing papers authored by Oier Mees

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Oier Mees

This figure shows the co-authorship network connecting the top 25 collaborators of Oier Mees. A scholar is included among the top collaborators of Oier Mees 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 Oier Mees. Oier Mees is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Pertsch, Karl, Brian Ichter, Danny Driess, et al.. (2025). FAST: Efficient Action Tokenization for Vision-Language-Action Models. 6 indexed citations

2.

Huang, Chenguang, Oier Mees, Andy Zeng, & Wolfram Burgard. (2025). Multimodal spatial language maps for robot navigation and manipulation. The International Journal of Robotics Research.

3.

Dasari, Sudeep, et al.. (2025). The Ingredients for Robotic Diffusion Transformers. 15617–15625. 1 indexed citations

4.

Mees, Oier, et al.. (2025). Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding. 5961–5968. 2 indexed citations

5.

Walke, Homer, Karl Pertsch, Kevin Black, et al.. (2024). Octo: An Open-Source Generalist Robot Policy. 29 indexed citations

6.

Huang, Chenguang, Oier Mees, Andy Zeng, & Wolfram Burgard. (2023). Visual Language Maps for Robot Navigation. 10608–10615. 160 indexed citations breakdown →

7.

Mees, Oier, et al.. (2023). Grounding Language with Visual Affordances over Unstructured Data. 11576–11582. 47 indexed citations

8.

Mees, Oier, et al.. (2022). Affordance Learning from Play for Sample-Efficient Policy Learning. 2022 International Conference on Robotics and Automation (ICRA). 6372–6378. 25 indexed citations

9.

Mees, Oier, et al.. (2022). What Matters in Language Conditioned Robotic Imitation Learning Over Unstructured Data. IEEE Robotics and Automation Letters. 7(4). 11205–11212. 40 indexed citations

10.

Mees, Oier, Maxim Tatarchenko, Thomas Brox, & Wolfram Burgard. (2019). Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics. 6083–6089. 10 indexed citations

11.

Mees, Oier, et al.. (2017). Metric learning for generalizing spatial relations to new objects. 9. 3175–3182. 13 indexed citations

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.

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