Davide Scaramuzza
Impact in
- Computer Vision and Pattern Recognition top 0.02%
- Advanced Vision and Imaging
- Robotic Path Planning Algorithms
- Advanced Image and Video Retrieval Techniques
- Aerospace Engineering top 0.01%
- Robotics and Sensor-Based Localization
Papers in
-
- Advanced Vision and Imaging 86
- Robotic Path Planning Algorithms 56
- Advanced Image and Video Retrieval Techniques 31
-
- Robotics and Sensor-Based Localization 149
- Co-authors
- Roland Siegwart (39 shared papers)Christian Förster (14 shared papers)Friedrich Fraundorfer (7 shared papers)Luca Carlone (7 shared papers)Matia Pizzoli (5 shared papers)Henri Rebecq (19 shared papers)Zichao Zhang (9 shared papers)Guillermo Gallego (18 shared papers)
- Journals
- IEEE Robotics and Automation Letters (38 papers)IEEE Transactions on Robotics (10 papers)Journal of Field Robotics (8 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (6 papers)International Journal of Computer Vision (5 papers)
- Partner nations
- SwitzerlandUnited StatesFrance
In The Last Decade
Davide Scaramuzza
251 papers receiving 22.8k citations
Davide Scaramuzza's Hit Papers
Peers
Comparison fields: 5 of 165
- Computer Vision and Pattern Recognition 14.5k
- Aerospace Engineering 15.4k
- Geology 3.1k
- Instrumentation 514
- Control and Systems Engineering 2.5k
Countries citing papers authored by Davide Scaramuzza
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
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-authors
The 25 scholars most cited alongside Davide Scaramuzza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 261 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age Hit paper breakdown → | 2016 | 2252 |
| 2 | SVO: Fast semi-direct monocular visual odometry Hit paper breakdown → | 2014 | 1443 |
| 3 | Visual Odometry [Tutorial] Hit paper breakdown → | 2011 | 1004 |
| 4 | On-Manifold Preintegration for Real-Time Visual--Inertial Odometry Hit paper breakdown → | 2016 | 1003 |
| 5 | SVO: Semidirect Visual Odometry for Monocular and Multicamera Systems Hit paper breakdown → | 2016 | 617 |
| 6 | A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry Hit paper breakdown → | 2018 | 457 |
| 7 | Event-Based Vision: A Survey Hit paper breakdown → | 2020 | 423 |
| 8 | A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots Hit paper breakdown → | 2015 | 418 |
| 9 | Visual Odometry : Part II: Matching, Robustness, Optimization, and Applications Hit paper breakdown → | 2012 | 410 |
| 10 | A Toolbox for Easily Calibrating Omnidirectional Cameras Hit paper breakdown → | 2006 | 377 |
| 11 | A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation Hit paper breakdown → | 2011 | 367 |
| 12 | IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation Hit paper breakdown → | 2015 | 343 |
| 13 | Champion-level drone racing using deep reinforcement learning Hit paper breakdown → | 2023 | 328 |
| 14 | 2018 | 320 | |
| 15 | Vision based MAV navigation in unknown and unstructured environments Hit paper breakdown → | 2010 | 311 |
| 16 | Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments Hit paper breakdown → | 2011 | 310 |
| 17 | 2006 | 300 | |
| 18 | A Benchmark Comparison of Monocular Visual-Inertial Odometry Algorithms for Flying Robots Hit paper breakdown → | 2018 | 286 |
| 19 | 2006 | 278 | |
| 20 | Differential Flatness of Quadrotor Dynamics Subject to Rotor Drag for Accurate Tracking of High-Speed Trajectories Hit paper breakdown → | 2017 | 272 |
About Davide Scaramuzza
Davide Scaramuzza is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Electrical and Electronic Engineering, Artificial Intelligence and Control and Systems Engineering, having authored 261 papers that have together received 23.7k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (149 papers), Advanced Vision and Imaging (86 papers), Robotic Path Planning Algorithms (56 papers), Advanced Memory and Neural Computing (42 papers), Advanced Image and Video Retrieval Techniques (31 papers), 3D Surveying and Cultural Heritage (23 papers), CCD and CMOS Imaging Sensors (23 papers) and Underwater Vehicles and Communication Systems (20 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (14.5k citations), Aerospace Engineering (15.4k citations), Geology (3.1k citations), Instrumentation (514 citations) and Control and Systems Engineering (2.5k citations). Davide Scaramuzza has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Roland Siegwart, Christian Förster, Friedrich Fraundorfer, Luca Carlone, Matia Pizzoli, Henri Rebecq, Zichao Zhang, Guillermo Gallego, Agostino Martinelli and Elias Mueggler. Their work appears in journals such as IEEE Robotics and Automation Letters, IEEE Transactions on Robotics, Journal of Field Robotics, IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Vision.
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.