Gerhard Rigoll

14.6k total citations · 1 hit paper
434 papers, 8.7k citations indexed

About

Gerhard Rigoll is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Gerhard Rigoll has authored 434 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 233 papers in Computer Vision and Pattern Recognition, 181 papers in Artificial Intelligence and 166 papers in Signal Processing. Recurrent topics in Gerhard Rigoll's work include Speech and Audio Processing (117 papers), Speech Recognition and Synthesis (107 papers) and Music and Audio Processing (94 papers). Gerhard Rigoll is often cited by papers focused on Speech and Audio Processing (117 papers), Speech Recognition and Synthesis (107 papers) and Music and Audio Processing (94 papers). Gerhard Rigoll collaborates with scholars based in Germany, Japan and China. Gerhard Rigoll's co-authors include Björn W. Schuller, M. Lang, Martin Wöllmer, Florian Eyben, Martin Hofmann, Mohammadreza Babaee, Philipp Tiefenbacher, Jürgen T. Geiger, A. Kosmala and Stefan Eickeler and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Gerhard Rigoll

417 papers receiving 8.0k citations

Hit Papers

Background segmentation with feedback: The Pixel-Based Ad... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gerhard Rigoll Germany 42 4.2k 3.2k 3.2k 2.5k 1.0k 434 8.7k
Stefanos Zafeiriou United Kingdom 52 8.5k 2.0× 1.9k 0.6× 3.0k 0.9× 2.5k 1.0× 380 0.4× 251 11.8k
Guodong Guo China 54 7.7k 1.8× 1.6k 0.5× 2.4k 0.8× 1.2k 0.5× 698 0.7× 235 10.1k
Iain Matthews United States 40 9.9k 2.4× 1.1k 0.4× 2.3k 0.7× 3.3k 1.3× 451 0.4× 114 12.7k
Fernando De la Torre United States 46 5.3k 1.3× 1.4k 0.4× 1.3k 0.4× 1.4k 0.6× 387 0.4× 157 7.8k
Qiang Ji United States 52 5.6k 1.3× 1.8k 0.5× 1.0k 0.3× 3.2k 1.3× 736 0.7× 316 11.2k
Stefanos Kollias Greece 34 2.8k 0.7× 1.7k 0.5× 1.2k 0.4× 1.6k 0.6× 232 0.2× 306 5.8k
Sérgio Escalera Spain 41 3.6k 0.9× 1.5k 0.4× 1.0k 0.3× 781 0.3× 824 0.8× 261 6.4k
Yingli Tian United States 48 8.3k 2.0× 2.4k 0.7× 719 0.2× 2.2k 0.9× 1.3k 1.3× 203 11.4k
Tadas Baltrušaitis United Kingdom 21 2.6k 0.6× 1.9k 0.6× 810 0.3× 1.7k 0.7× 293 0.3× 51 6.4k
Sridha Sridharan Australia 44 3.9k 0.9× 3.2k 1.0× 3.2k 1.0× 534 0.2× 560 0.6× 480 8.3k

Countries citing papers authored by Gerhard Rigoll

Since Specialization
Citations

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

Fields of papers citing papers by Gerhard Rigoll

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gerhard Rigoll

This figure shows the co-authorship network connecting the top 25 collaborators of Gerhard Rigoll. A scholar is included among the top collaborators of Gerhard Rigoll 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 Gerhard Rigoll. Gerhard Rigoll 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
2.
Yan, Jun, et al.. (2024). Efficient Interaction-Aware Trajectory Prediction Model Based on Multi-head Attention. Automotive Innovation. 7(2). 258–270. 5 indexed citations
3.
Rigoll, Gerhard, et al.. (2024). CSANet: Cuboid-Wise Shape Augmentation 3D Object Detector for Occluded Targets. IEEE Signal Processing Letters. 31. 1750–1754.
4.
Yan, Jun, et al.. (2023). An Adversarial Attack on Salient Regions of Traffic Sign. Automotive Innovation. 6(2). 190–203. 4 indexed citations
5.
Yin, Huilin, et al.. (2023). FSFNet: Foreground Score-Aware Fusion for 3-D Object Detector Under Unfavorable Conditions. IEEE Sensors Journal. 23(14). 15988–16001. 1 indexed citations
6.
Yin, Huilin, et al.. (2022). Improved 3D Object Detector Under Snowfall Weather Condition Based on LiDAR Point Cloud. IEEE Sensors Journal. 22(16). 16276–16292. 14 indexed citations
7.
Babaee, Mohammadreza, Reza Bahmanyar, Gerhard Rigoll, & Mihai Datcu. (2014). Interactive clustering for SAR image understanding. elib (German Aerospace Center). 1–4. 1 indexed citations
8.
Weninger, Felix, Shinji Watanabe, Jonathan Le Roux, et al.. (2014). The MERL/MELCO/TUM system for the REVERB Challenge using Deep Recurrent Neural Network Feature Enhancement. International Conference on Acoustics, Speech, and Signal Processing. 23 indexed citations
9.
Rigoll, Gerhard, et al.. (2014). Immersive Visualization of SAR Images using Nonnegative Matrix Factorization. elib (German Aerospace Center). 22(4-5). 385–388. 9 indexed citations
10.
Weninger, Felix, Jürgen T. Geiger, Martin Wöllmer, Björn W. Schuller, & Gerhard Rigoll. (2013). The Munich Feature Enhancement Approach to the 2013 CHiME Challenge Using BLSTM Recurrent Neural Networks. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 14 indexed citations
11.
Hofmann, Martin, Philipp Tiefenbacher, & Gerhard Rigoll. (2012). Background segmentation with feedback: The Pixel-Based Adaptive Segmenter. 38–43. 426 indexed citations breakdown →
12.
Wöllmer, Martin, Florian Eyben, Alex Graves, Björn W. Schuller, & Gerhard Rigoll. (2009). A Tandem BLSTM-DBN Architecture for Keyword Spotting with Enhanced Context Modeling. 12 indexed citations
13.
Schuller, Björn W., et al.. (2008). One Day in Half an Hour: Music Thumbnailing Incorporating Harmony- and Rhythm Structure. 3 indexed citations
14.
Kohlbecher, Stefan, et al.. (2007). Gaze vector detection by stereo reconstruction of the pupil contours (Abstract ECE 2007). Journal of Eye Movement Research. 1(1). 121. 1 indexed citations
15.
Dielmann, Alfred, Daniel Gática-Pérez, S.A. Reiter, et al.. (2006). Multimodal Integration for Meeting Group Action Segmentation and Recognition. Lecture notes in computer science. 52–63. 17 indexed citations
16.
Rigoll, Gerhard, et al.. (2006). A context-adaptive search engine concept and multimodal input strategies for automotive environments.
17.
Lang, Manfred, et al.. (2003). Towards Multimodal Error Management: Experimental Evaluation of User Strategies in Event of Faulty Application Behavior in Automotive Environments. SHILAP Revista de lepidopterología. 2 indexed citations
18.
Wallhoff, Frank & Gerhard Rigoll. (2003). Synthesis and Recognition of Face Profiles. Vision Modeling and Visualization. 545–552. 1 indexed citations
19.
Rigoll, Gerhard, et al.. (1998). Controlling the Complexity of HMM Systems by Regularization. Neural Information Processing Systems. 11. 737–743. 6 indexed citations
20.
Rigoll, Gerhard, A. Kosmala, & Stefan Eickeler. (1998). High Performance Real-Time Gesture Recognition Using Hidden Markov Models. 5 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026