Davide Scaramuzza

37.6k total citations · 22 hit papers
257 papers, 23.0k citations indexed

About

Davide Scaramuzza is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Davide Scaramuzza has authored 257 papers receiving a total of 23.0k indexed citations (citations by other indexed papers that have themselves been cited), including 159 papers in Computer Vision and Pattern Recognition, 154 papers in Aerospace Engineering and 57 papers in Electrical and Electronic Engineering. Recurrent topics in Davide Scaramuzza's work include Robotics and Sensor-Based Localization (148 papers), Advanced Vision and Imaging (85 papers) and Robotic Path Planning Algorithms (56 papers). Davide Scaramuzza is often cited by papers focused on Robotics and Sensor-Based Localization (148 papers), Advanced Vision and Imaging (85 papers) and Robotic Path Planning Algorithms (56 papers). Davide Scaramuzza collaborates with scholars based in Switzerland, United States and France. Davide Scaramuzza's co-authors include Roland Siegwart, Christian Förster, Friedrich Fraundorfer, Luca Carlone, Matia Pizzoli, Henri Rebecq, Zichao Zhang, Guillermo Gallego, Agostino Martinelli and Elias Mueggler and has published in prestigious journals such as Nature, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Davide Scaramuzza

248 papers receiving 22.2k citations

Hit Papers

Past, present, and future of simultaneous localization... 2010 2026 2015 2020 2016 2014 2011 2016 2016 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Davide Scaramuzza Switzerland 79 15.3k 14.3k 5.5k 3.1k 2.4k 257 23.0k
Frank Dellaert United States 55 10.0k 0.7× 8.6k 0.6× 3.6k 0.7× 1.7k 0.5× 1.5k 0.6× 209 15.3k
Dieter Fox United States 71 8.3k 0.5× 11.0k 0.8× 3.2k 0.6× 1.4k 0.4× 4.0k 1.6× 209 19.8k
Andrew J. Davison United Kingdom 46 11.3k 0.7× 11.6k 0.8× 2.6k 0.5× 3.5k 1.1× 1.2k 0.5× 108 15.9k
Kurt Konolige United States 43 9.6k 0.6× 10.7k 0.7× 2.0k 0.4× 1.8k 0.6× 1.4k 0.6× 106 15.3k
Ian Reid United Kingdom 63 9.2k 0.6× 16.0k 1.1× 2.2k 0.4× 2.3k 0.7× 889 0.4× 260 20.4k
Richard Hartley Australia 55 11.0k 0.7× 20.9k 1.5× 2.0k 0.4× 2.7k 0.9× 805 0.3× 216 27.1k
Hugh Durrant‐Whyte Australia 59 15.0k 1.0× 8.7k 0.6× 5.8k 1.1× 1.2k 0.4× 4.2k 1.7× 274 23.9k
Daniel Cremers Germany 71 11.2k 0.7× 17.6k 1.2× 2.0k 0.4× 3.9k 1.3× 769 0.3× 356 22.6k
Shaojie Shen Hong Kong 47 7.8k 0.5× 6.9k 0.5× 1.7k 0.3× 1.7k 0.6× 1.5k 0.6× 177 10.5k
Marc Pollefeys Switzerland 76 11.1k 0.7× 17.8k 1.2× 1.2k 0.2× 3.9k 1.3× 1.1k 0.5× 464 22.0k

Countries citing papers authored by Davide Scaramuzza

Since Specialization
Citations

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

Fields of papers citing papers by Davide Scaramuzza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Davide Scaramuzza

This figure shows the co-authorship network connecting the top 25 collaborators of Davide Scaramuzza. A scholar is included among the top collaborators of Davide Scaramuzza 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 Davide Scaramuzza. Davide Scaramuzza 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.
Cioffi, Giovanni, et al.. (2025). LiDAR Registration with Visual Foundation Models.
2.
Billard, Aude, Alin Albu‐Schäffer, Michael Beetz, et al.. (2025). A roadmap for AI in robotics. Nature Machine Intelligence. 7(6). 818–824. 1 indexed citations
3.
4.
Hanover, Drew, Antonio Loquercio, Leonard Bauersfeld, et al.. (2024). Autonomous Drone Racing: A Survey. IEEE Transactions on Robotics. 40. 3044–3067. 37 indexed citations
5.
Romero, Ángel, Yunlong Song, & Davide Scaramuzza. (2024). Actor-Critic Model Predictive Control. 14777–14784. 27 indexed citations
6.
Kim, Daekyum, et al.. (2024). Wearable robots for the real world need vision. Science Robotics. 9(90). eadj8812–eadj8812. 8 indexed citations
7.
Ayyad, Abdulla, et al.. (2024). E-Calib: A Fast, Robust, and Accurate Calibration Toolbox for Event Cameras. IEEE Transactions on Image Processing. 33. 3977–3990. 13 indexed citations
8.
Gehrig, Mathias & Davide Scaramuzza. (2023). Recurrent Vision Transformers for Object Detection with Event Cameras. 13884–13893. 79 indexed citations
9.
Scaramuzza, Davide, et al.. (2023). E-NeRF: Neural Radiance Fields From a Moving Event Camera. IEEE Robotics and Automation Letters. 8(3). 1587–1594. 34 indexed citations
10.
Yang, Yanchao, Antonio Loquercio, Davide Scaramuzza, & Stefano Soatto. (2019). Unsupervised Moving Object Detection via Contextual Information Separation. 879–888. 74 indexed citations
11.
Gehrig, Daniel, Mathias Gehrig, Javier Hidalgo‐Carrió, & Davide Scaramuzza. (2019). Video to Events: Bringing Modern Computer Vision Closer to Event Cameras.. arXiv (Cornell University). 6 indexed citations
12.
Palossi, Daniele, Antonio Loquercio, Francesco Conti, et al.. (2019). A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones. IEEE Internet of Things Journal. 6(5). 8357–8371. 120 indexed citations
13.
Sanket, Nitin J., et al.. (2019). EVDodge: Embodied AI For High-Speed Dodging On A Quadrotor Using Event Cameras.. arXiv (Cornell University). 9 indexed citations
14.
Loquercio, Antonio, Ana I. Maqueda, Carlos R. del‐Blanco, & Davide Scaramuzza. (2018). DroNet: Learning to Fly by Driving. IEEE Robotics and Automation Letters. 3(2). 1088–1095. 317 indexed citations
15.
Cieslewski, Titus, Elia Kaufmann, & Davide Scaramuzza. (2017). Rapid exploration with multi-rotors: A frontier selection method for high speed flight. Zurich Open Repository and Archive (University of Zurich). 2135–2142. 148 indexed citations
16.
Gallego, Guillermo, et al.. (2017). Event-Based, 6-DOF Camera Tracking from Photometric Depth Maps. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(10). 2402–2412. 122 indexed citations
17.
Falanga, Davide, Elias Mueggler, Matthias Faessler, & Davide Scaramuzza. (2016). Aggressive Quadrotor Flight through Narrow Gaps with Onboard Sensing and Computing.. arXiv (Cornell University). 9 indexed citations
18.
Mueggler, Elias, Henri Rebecq, Guillermo Gallego, Tobi Delbrück, & Davide Scaramuzza. (2016). The Event-Camera Dataset: Event-based Data for Pose Estimation, Visual Odometry, and SLAM. arXiv (Cornell University). 3 indexed citations
19.
Pizzoli, Matia, Christian Förster, & Davide Scaramuzza. (2014). REMODE: Probabilistic, monocular dense reconstruction in real time. Zurich Open Repository and Archive (University of Zurich). 2609–2616. 237 indexed citations
20.
Scaramuzza, Davide, Agostino Martinelli, & Roland Siegwart. (2006). A Toolbox for Easily Calibrating Omnidirectional Cameras. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 5695–5701. 370 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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