Martin Sundermeyer

4.4k total citations · 2 hit papers
26 papers, 2.3k citations indexed

About

Martin Sundermeyer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, Martin Sundermeyer has authored 26 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 8 papers in Aerospace Engineering. Recurrent topics in Martin Sundermeyer's work include Natural Language Processing Techniques (13 papers), Speech Recognition and Synthesis (12 papers) and Topic Modeling (9 papers). Martin Sundermeyer is often cited by papers focused on Natural Language Processing Techniques (13 papers), Speech Recognition and Synthesis (12 papers) and Topic Modeling (9 papers). Martin Sundermeyer collaborates with scholars based in Germany, France and China. Martin Sundermeyer's co-authors include Hermann Ney, Ralf Schlüter, Rudolph Triebel, Tamer Alkhouli, Joern Wuebker, Maximilian Durner, Zoltán-Csaba Márton, Zoltán Tüske, Ilya Oparin and J.-L. Gauvain and has published in prestigious journals such as International Journal of Computer Vision, IEEE/ACM Transactions on Audio Speech and Language Processing and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Martin Sundermeyer

24 papers receiving 2.1k citations

Hit Papers

LSTM neural networks for language modeling 2012 2026 2016 2021 2012 2015 400 800 1.2k
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.

  1. LSTM neural networks for language modeling
    2012 1.2k citations Martin Sundermeyer, Ralf Schlüter et al. profile →
  2. From Feedforward to Recurrent LSTM Neural Networks for Language Modeling
    2015 360 citations Martin Sundermeyer, Hermann Ney et al. IEEE/ACM Transactions on Audio Speech and Language Processing profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Sundermeyer Germany 17 1.3k 533 343 207 177 26 2.3k
Hadi Sadoghi Yazdi Iran 22 885 0.7× 489 0.9× 233 0.7× 212 1.0× 119 0.7× 184 2.0k
Hang Su China 20 1.3k 1.0× 650 1.2× 195 0.6× 125 0.6× 124 0.7× 88 2.3k
Nikunj C. Oza United States 21 1.4k 1.1× 355 0.7× 347 1.0× 189 0.9× 111 0.6× 70 2.2k
Hujun Yin United Kingdom 27 948 0.7× 1.0k 1.9× 273 0.8× 233 1.1× 101 0.6× 164 2.5k
Timothy C. Havens United States 24 1.3k 1.0× 611 1.1× 280 0.8× 121 0.6× 237 1.3× 150 2.5k
Stanley C. Ahalt United States 19 715 0.5× 543 1.0× 258 0.8× 140 0.7× 91 0.5× 110 1.6k
宏治 津田 Japan 1 1.1k 0.8× 867 1.6× 165 0.5× 135 0.7× 67 0.4× 2 2.0k
Yunhai Tong China 22 959 0.7× 709 1.3× 428 1.2× 128 0.6× 68 0.4× 72 1.9k
Fanzhang Li China 23 906 0.7× 1.1k 2.1× 217 0.6× 207 1.0× 58 0.3× 139 2.3k
Ausif Mahmood United States 20 1.0k 0.8× 767 1.4× 282 0.8× 181 0.9× 69 0.4× 72 2.9k

Countries citing papers authored by Martin Sundermeyer

Since Specialization
Citations

This map shows the geographic impact of Martin Sundermeyer'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 Martin Sundermeyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Sundermeyer more than expected).

Fields of papers citing papers by Martin Sundermeyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Sundermeyer. 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 Martin Sundermeyer. The network helps show where Martin Sundermeyer may publish in the future.

Co-authorship network of co-authors of Martin Sundermeyer

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

All Works

20 of 20 papers shown
1.
Yan, Bin, Martin Sundermeyer, David Joseph Tan, Huchuan Lu, & Federico Tombari. (2025). Towards Real-Time Open-Vocabulary Video Instance Segmentation. 1861–1871.
2.
Di, Yan, Martin Sundermeyer, Fabian Manhardt, et al.. (2024). HiPose: Hierarchical Binary Surface Encoding and Correspondence Pruning for RGB-D 6DoF Object Pose Estimation. 10148–10158. 5 indexed citations
3.
Hodaň, Tomáš, Martin Sundermeyer, Yann Labbé, et al.. (2024). BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objects. 5610–5619. 14 indexed citations
4.
Sundermeyer, Martin, et al.. (2023). BlenderProc2: A Procedural Pipeline for PhotorealisticRendering. The Journal of Open Source Software. 8(82). 4901–4901. 55 indexed citations
5.
Durner, Maximilian, et al.. (2023). 6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics. elib (German Aerospace Center). 10749–10756. 11 indexed citations
6.
Sundermeyer, Martin, Tomáš Hodaň, Yann Labbé, et al.. (2023). BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects. 2785–2794. 31 indexed citations
7.
Müller, Marcus, Maximilian Durner, Martin Sundermeyer, et al.. (2021). Rock Instance Segmentation from Synthetic Images for Planetary Exploration Missions. elib (German Aerospace Center). 4 indexed citations
8.
Sundermeyer, Martin, et al.. (2020). BlenderProc: Reducing the Reality Gap with Photorealistic Rendering. elib (German Aerospace Center). 36 indexed citations
9.
Sundermeyer, Martin, Zoltán-Csaba Márton, Maximilian Durner, & Rudolph Triebel. (2019). Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection. International Journal of Computer Vision. 128(3). 714–729. 86 indexed citations
10.
Sundermeyer, Martin, Hermann Ney, & Francisco Casacuberta. (2017). Improvements in language and translation modeling. RWTH Publications (RWTH Aachen). 3 indexed citations
11.
Sundermeyer, Martin, Hermann Ney, & Ralf Schlüter. (2015). From Feedforward to Recurrent LSTM Neural Networks for Language Modeling. IEEE/ACM Transactions on Audio Speech and Language Processing. 23(3). 517–529. 360 indexed citations breakdown →
12.
Sundermeyer, Martin, Tamer Alkhouli, Joern Wuebker, & Hermann Ney. (2014). Translation Modeling with Bidirectional Recurrent Neural Networks. 14–25. 118 indexed citations
13.
Sundermeyer, Martin, Ralf Schlüter, & Hermann Ney. (2014). rwthlm — the RWTH aachen university neural network language modeling toolkit. 2093–2097. 28 indexed citations
14.
Sundermeyer, Martin, et al.. (2013). Comparison of feedforward and recurrent neural network language models. 8430–8434. 80 indexed citations
15.
Sundermeyer, Martin, Ralf Schlüter, & Hermann Ney. (2012). LSTM neural networks for language modeling. 194–197. 1226 indexed citations breakdown →
16.
Tüske, Zoltán, Martin Sundermeyer, Ralf Schlüter, & Hermann Ney. (2012). Context-dependent MLPs for LVCSR: TANDEM, hybrid or both?. 22 indexed citations
17.
Oparin, Ilya, Martin Sundermeyer, Hermann Ney, & Jean‐Luc Gauvain. (2012). Performance analysis of Neural Networks in combination with n-gram language models. 5005–5008. 21 indexed citations
18.
Sundermeyer, Martin, Simon Wiesler, Christian Plahl, et al.. (2011). The RWTH 2010 Quaero ASR evaluation system for English, French, and German. 36 indexed citations
19.
Sundermeyer, Martin, Ralf Schlüter, & Hermann Ney. (2011). On the estimation of discount parameters for language model smoothing. 1433–1436. 20 indexed citations
20.
Wiesler, Simon, Martin Sundermeyer, Christian Plahl, et al.. (2010). The RWTH 2009 quaero ASR evaluation system for English and German. 1517–1520. 16 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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