César Cadena

7.7k total citations · 2 hit papers
90 papers, 4.6k citations indexed

About

César Cadena is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Environmental Engineering. According to data from OpenAlex, César Cadena has authored 90 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Aerospace Engineering, 62 papers in Computer Vision and Pattern Recognition and 13 papers in Environmental Engineering. Recurrent topics in César Cadena's work include Robotics and Sensor-Based Localization (65 papers), Advanced Image and Video Retrieval Techniques (24 papers) and Advanced Neural Network Applications (20 papers). César Cadena is often cited by papers focused on Robotics and Sensor-Based Localization (65 papers), Advanced Image and Video Retrieval Techniques (24 papers) and Advanced Neural Network Applications (20 papers). César Cadena collaborates with scholars based in Switzerland, Spain and United States. César Cadena's co-authors include José Neira, Yasir Latif, Ian Reid, John J. Leonard, Davide Scaramuzza, Henry Carrillo, Luca Carlone, Roland Siegwart, Juan Nieto and Marco Hutter and has published in prestigious journals such as Sensors, International Journal of Computer Vision and The International Journal of Robotics Research.

In The Last Decade

César Cadena

85 papers receiving 4.4k citations

Hit Papers

Past, present, and future of simultaneous localization an... 2016 2026 2019 2022 2016 2019 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
César Cadena Switzerland 28 3.4k 3.0k 910 788 546 90 4.6k
Margarita Chli Switzerland 31 4.4k 1.3× 4.6k 1.6× 1.1k 1.2× 805 1.0× 437 0.8× 84 6.4k
Paul Furgale Switzerland 31 4.0k 1.2× 3.0k 1.0× 1.1k 1.2× 1.0k 1.3× 342 0.6× 56 4.7k
Edwin Olson United States 28 2.2k 0.7× 2.2k 0.7× 726 0.8× 479 0.6× 513 0.9× 72 4.2k
Brendan Englot United States 23 3.5k 1.0× 2.3k 0.8× 744 0.8× 1.2k 1.5× 399 0.7× 73 4.4k
Juan Nieto Switzerland 41 2.9k 0.8× 2.6k 0.9× 760 0.8× 449 0.6× 1.0k 1.9× 143 5.2k
Guoquan Huang United States 33 3.5k 1.0× 2.1k 0.7× 1.3k 1.5× 1.0k 1.3× 495 0.9× 131 4.0k
Timothy D. Barfoot Canada 33 2.7k 0.8× 1.9k 0.7× 699 0.8× 443 0.6× 707 1.3× 175 4.1k
J. M. M. Montiel Spain 28 3.5k 1.0× 3.0k 1.0× 914 1.0× 740 0.9× 361 0.7× 68 4.5k
T. Bailey Australia 12 4.2k 1.2× 2.7k 0.9× 1.8k 2.0× 730 0.9× 887 1.6× 20 5.3k
Friedrich Fraundorfer Austria 26 3.3k 1.0× 3.1k 1.1× 511 0.6× 754 1.0× 216 0.4× 125 4.4k

Countries citing papers authored by César Cadena

Since Specialization
Citations

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

Fields of papers citing papers by César Cadena

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of César Cadena

This figure shows the co-authorship network connecting the top 25 collaborators of César Cadena. A scholar is included among the top collaborators of César Cadena 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 César Cadena. César Cadena 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.
Leutenegger, Stefan, et al.. (2025). FrontierNet: Learning Visual Cues to Explore. IEEE Robotics and Automation Letters. 10(7). 6576–6583.
2.
Yang, Fan, Yuheng Qiu, César Cadena, et al.. (2025). TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation. Open MIND. 20524–20531. 1 indexed citations
3.
Talbot, William Henry Fox, Julian Nubert, César Cadena, et al.. (2025). Continuous-Time State Estimation Methods in Robotics: A Survey. IEEE Transactions on Robotics. 41. 4975–4999. 4 indexed citations
4.
5.
Oleynikova, Helen, et al.. (2024). COIN-LIO: Complementary Intensity-Augmented LiDAR Inertial Odometry. 1730–1737. 12 indexed citations
7.
Chebrolu, Nived, et al.. (2023). Fast Traversability Estimation for Wild Visual Navigation. 42 indexed citations
8.
Cramariuc, Andrei, et al.. (2023). Path-Constrained State Estimation for Rail Vehicles. Repository for Publications and Research Data (ETH Zurich). 4600–4607.
9.
Reijgwart, Victor, César Cadena, Roland Siegwart, & Lionel Ott. (2023). Efficient volumetric mapping of multi-scale environments using wavelet-based compression. 8 indexed citations
10.
Schneider, Thomas, Mingyang Li, César Cadena, Juan Nieto, & Roland Siegwart. (2019). Observability-Aware Self-Calibration of Visual and Inertial Sensors for Ego-Motion Estimation. IEEE Sensors Journal. 19(10). 3846–3860. 42 indexed citations
11.
Wellhausen, Lorenz, Alexey Dosovitskiy, René Ranftl, et al.. (2019). Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning. IEEE Robotics and Automation Letters. 4(2). 1509–1516. 144 indexed citations
12.
Tschopp, Florian, Thomas Schneider, Andrew W. Palmer, et al.. (2019). Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles. IEEE Robotics and Automation Letters. 4(2). 1815–1822. 31 indexed citations
13.
Bürki, Mathias, Marcin Dymczyk, Renaud Dubé, et al.. (2019). VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments. 1124–1130. 13 indexed citations
14.
Blum, Hermann, Paul-Edouard Sarlin, Juan Nieto, Roland Siegwart, & César Cadena. (2019). Fishyscapes: A Benchmark for Safe Semantic Segmentation in Autonomous Driving. 2403–2412. 60 indexed citations
15.
Dubé, Renaud, Hannes Sommer, Igor Gilitschenski, et al.. (2018). Incremental-Segment-Based Localization in 3-D Point Clouds. IEEE Robotics and Automation Letters. 3(3). 1832–1839. 48 indexed citations
16.
Pfeiffer, Mark G., Matteo Turchetta, César Cadena, et al.. (2018). Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations. IEEE Robotics and Automation Letters. 3(4). 4423–4430. 122 indexed citations
17.
Bürki, Mathias, Marcin Dymczyk, Igor Gilitschenski, et al.. (2018). Map Management for Efficient Long-Term Visual Localization in Outdoor Environments. 682–688. 24 indexed citations
18.
Wellhausen, Lorenz, Renaud Dubé, Abel Gawel, Roland Siegwart, & César Cadena. (2017). Reliable Real-time Change Detection and Mapping for 3D LiDARs. Repository for Publications and Research Data (ETH Zurich). 81–87. 5 indexed citations
19.
Cadena, César, Luca Carlone, Henry Carrillo, et al.. (2016). Simultaneous Localization And Mapping: Present, Future, and the Robust-Perception Age.. arXiv (Cornell University). 51 indexed citations
20.
Dubé, Renaud, Abel Gawel, César Cadena, et al.. (2016). 3D Localization, Mapping and Path Planning for Search and Rescue Operations. Repository for Publications and Research Data (ETH Zurich). 272–273. 6 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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