Thomas Läbe

814 total citations
22 papers, 518 citations indexed

About

Thomas Läbe is a scholar working on Computer Vision and Pattern Recognition, Plant Science and Aerospace Engineering. According to data from OpenAlex, Thomas Läbe has authored 22 papers receiving a total of 518 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 11 papers in Plant Science and 9 papers in Aerospace Engineering. Recurrent topics in Thomas Läbe's work include Smart Agriculture and AI (10 papers), Robotics and Sensor-Based Localization (9 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Thomas Läbe is often cited by papers focused on Smart Agriculture and AI (10 papers), Robotics and Sensor-Based Localization (9 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Thomas Läbe collaborates with scholars based in Germany, United Kingdom and United States. Thomas Läbe's co-authors include Cyrill Stachniss, Nived Chebrolu, Jens Behley, Federico Magistri, Andres Milioto, Xieyuanli Chen, Johannes Schneider, Philipp Lottes, Wolfgang Förstner and Chris McCool and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Atmospheric chemistry and physics.

In The Last Decade

Thomas Läbe

20 papers receiving 501 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Läbe Germany 15 227 211 190 150 111 22 518
Nived Chebrolu Germany 14 209 0.9× 209 1.0× 483 2.5× 264 1.8× 113 1.0× 26 840
André Aguiar Portugal 10 135 0.6× 108 0.5× 171 0.9× 82 0.5× 33 0.3× 18 350
Steven W. Chen United States 9 159 0.7× 160 0.8× 350 1.8× 142 0.9× 49 0.4× 10 693
Supreeth Achar United States 12 210 0.9× 383 1.8× 368 1.9× 119 0.8× 41 0.4× 21 860
Dimitris Zermas United States 8 163 0.7× 166 0.8× 131 0.7× 219 1.5× 99 0.9× 10 441
Tom Botterill New Zealand 14 256 1.1× 266 1.3× 167 0.9× 83 0.6× 52 0.5× 29 563
Robert Cupec Croatia 12 170 0.7× 207 1.0× 116 0.6× 59 0.4× 45 0.4× 46 442
Wolfgang Förstner Germany 14 119 0.5× 325 1.5× 139 0.7× 264 1.8× 148 1.3× 33 750
Ruifang Zhai China 12 50 0.2× 102 0.5× 124 0.7× 189 1.3× 118 1.1× 51 475
Wera Winterhalter Germany 4 112 0.5× 84 0.4× 315 1.7× 61 0.4× 32 0.3× 4 424

Countries citing papers authored by Thomas Läbe

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Läbe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Läbe

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Läbe. A scholar is included among the top collaborators of Thomas Läbe 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 Thomas Läbe. Thomas Läbe 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.
Nunes, Lucas, et al.. (2025). SfmOcc: Vision-Based 3D Semantic Occupancy Prediction in Urban Environments. IEEE Robotics and Automation Letters. 10(5). 5074–5081.
2.
Magistri, Federico, Thomas Läbe, Yue Pan, et al.. (2025). A Dataset and Benchmark for Shape Completion of Fruits for Agricultural Robotics. 16774–16780. 1 indexed citations
3.
Wiesmann, Louis, Thomas Läbe, Lucas Nunes, Jens Behley, & Cyrill Stachniss. (2024). Joint Intrinsic and Extrinsic Calibration of Perception Systems Utilizing a Calibration Environment. IEEE Robotics and Automation Letters. 9(10). 9103–9110.
4.
Läbe, Thomas, et al.. (2023). Panoptic Segmentation With Partial Annotations for Agricultural Robots. IEEE Robotics and Automation Letters. 9(2). 1660–1667. 2 indexed citations
5.
Läbe, Thomas, et al.. (2023). Towards Domain Generalization in Crop and Weed Segmentation for Precision Farming Robots. IEEE Robotics and Automation Letters. 8(6). 3310–3317. 19 indexed citations
6.
Pan, Yue, Federico Magistri, Thomas Läbe, et al.. (2023). Panoptic Mapping with Fruit Completion and Pose Estimation for Horticultural Robots. 4226–4233. 13 indexed citations
7.
Halstead, Michael, et al.. (2023). PAg-NeRF: Towards Fast and Efficient End-to-End Panoptic 3D Representations for Agricultural Robotics. IEEE Robotics and Automation Letters. 9(1). 907–914. 14 indexed citations
8.
Magistri, Federico, Ignacio Vizzo, Thomas Läbe, et al.. (2022). Contrastive 3D Shape Completion and Reconstruction for Agricultural Robots Using RGB-D Frames. IEEE Robotics and Automation Letters. 7(4). 10120–10127. 34 indexed citations
9.
Wiesmann, Louis, et al.. (2022). Robust Onboard Localization in Changing Environments Exploiting Text Spotting. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 917–924. 16 indexed citations
10.
Chebrolu, Nived, Federico Magistri, Thomas Läbe, & Cyrill Stachniss. (2021). Registration of spatio-temporal point clouds of plants for phenotyping. PLoS ONE. 16(2). e0247243–e0247243. 32 indexed citations
11.
Chen, Xieyuanli, et al.. (2021). OverlapNet: a siamese network for computing LiDAR scan similarity with applications to loop closing and localization. Autonomous Robots. 46(1). 61–81. 90 indexed citations
12.
Chebrolu, Nived, Thomas Läbe, & Cyrill Stachniss. (2020). Spatio-Temporal Non-Rigid Registration of 3D Point Clouds of Plants. 3112–3118. 28 indexed citations
13.
Chebrolu, Nived, Philipp Lottes, Thomas Läbe, & Cyrill Stachniss. (2019). Robot Localization Based on Aerial Images for Precision Agriculture Tasks in Crop Fields. 1787–1793. 38 indexed citations
14.
Chebrolu, Nived, Thomas Läbe, & Cyrill Stachniss. (2018). Robust Long-Term Registration of UAV Images of Crop Fields for Precision Agriculture. IEEE Robotics and Automation Letters. 3(4). 3097–3104. 61 indexed citations
15.
Kicherer, Anna, Katja Herzog, Andreas Backhaus, et al.. (2017). Phenoliner: A New Field Phenotyping Platform for Grapevine Research. Sensors. 17(7). 1625–1625. 36 indexed citations
16.
Schneider, Johannes, et al.. (2016). Cloud photogrammetry with dense stereo for fisheye cameras. Atmospheric chemistry and physics. 16(22). 14231–14248. 23 indexed citations
17.
Läbe, Thomas, et al.. (2015). 1 Trajectory Reconstruction Using Long Sequences of Digital Images From an Omnidirectional Camera. 3 indexed citations
18.
Schneider, Johannes, Thomas Läbe, & Wolfgang Förstner. (2013). INCREMENTAL REAL-TIME BUNDLE ADJUSTMENT FOR MULTI-CAMERA SYSTEMS WITH POINTS AT INFINITY. SHILAP Revista de lepidopterología. XL-1/W2. 355–360. 19 indexed citations
19.
Läbe, Thomas. (2012). GEOMETRIC STABILITY OF LOW-COST DIGITAL CONSUMER CAMERAS. 25 indexed citations
20.
Läbe, Thomas, et al.. (2008). AUTOMATIC RELATIVE ORIENTATION OF IMAGES 1. 21 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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