Gabriele Berton

580 total citations
14 papers, 289 citations indexed

About

Gabriele Berton is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Ocean Engineering. According to data from OpenAlex, Gabriele Berton has authored 14 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 10 papers in Aerospace Engineering and 2 papers in Ocean Engineering. Recurrent topics in Gabriele Berton's work include Advanced Image and Video Retrieval Techniques (11 papers), Robotics and Sensor-Based Localization (10 papers) and Multimodal Machine Learning Applications (7 papers). Gabriele Berton is often cited by papers focused on Advanced Image and Video Retrieval Techniques (11 papers), Robotics and Sensor-Based Localization (10 papers) and Multimodal Machine Learning Applications (7 papers). Gabriele Berton collaborates with scholars based in Italy, United States and Czechia. Gabriele Berton's co-authors include Carlo Masone, Barbara Caputo, Torsten Sattler, Gabriela Csurka, Riccardo Mereu, Francesco Montagna, Juán Martínez de Aragón and Alex Stoken and has published in prestigious journals such as IEEE Robotics and Automation Letters, Frontiers in Robotics and AI and Frontiers in Computer Science.

In The Last Decade

Gabriele Berton

12 papers receiving 287 citations

Peers

Gabriele Berton

CVPR

AE

EEE

HI

GEOLO

Federico Camposeco Switzerland

Daniel DeTone United States

Jared Heinly United States

Jana Nosková Czechia

Karel Lebeda United Kingdom

Miroslav Trajković Australia

Filip Radenović Czechia

Carl Toft Sweden

Nicholas A. Lord United Kingdom

Federico Camposeco Switzerland

Gabriele Berton

217 ×0.9

CVPR

194 ×0.9

AE

42 ×0.7

EEE

8 ×0.3

HI

83 ×3.6

GEOLO

Citations per year, relative to Gabriele Berton Gabriele Berton (= 1×) peers Federico Camposeco

Countries citing papers authored by Gabriele Berton

Since Specialization

Citations

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

Fields of papers citing papers by Gabriele Berton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabriele Berton

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriele Berton. A scholar is included among the top collaborators of Gabriele Berton 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 Gabriele Berton. Gabriele Berton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Berton, Gabriele & Carlo Masone. (2025). MegaLoc: One Retrieval to Place Them All. 2852–2858.

2.

Berton, Gabriele, et al.. (2024). EarthMatch: Iterative Coregistration for Fine-grained Localization of Astronaut Photography. 4264–4274. 1 indexed citations

3.

Berton, Gabriele, Alex Stoken, Barbara Caputo, & Carlo Masone. (2024). EarthLoc: Astronaut Photography Localization by Indexing Earth from Space. 8. 12754–12764. 1 indexed citations

4.

Berton, Gabriele, et al.. (2024). Distributed training of CosPlace for large-scale visual place recognition. Frontiers in Robotics and AI. 11. 1386464–1386464.

5.

Berton, Gabriele, et al.. (2024). Collaborative Visual Place Recognition through Federated Learning. 4215–4225. 1 indexed citations

6.

Berton, Gabriele, et al.. (2023). EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognition. 11046–11056. 48 indexed citations

7.

Berton, Gabriele, et al.. (2023). Divide&Classify: Fine-Grained Classification for City-Wide Visual Place Recognition. 11108–11118. 1 indexed citations

8.

Berton, Gabriele, et al.. (2023). JIST: Joint Image and Sequence Training for Sequential Visual Place Recognition. IEEE Robotics and Automation Letters. 9(2). 1310–1317. 3 indexed citations

9.

Berton, Gabriele, et al.. (2023). Are Local Features All You Need for Cross-Domain Visual Place Recognition?. 6155–6165. 13 indexed citations

10.

Berton, Gabriele, et al.. (2022). Adaptive-Attentive Geolocalization From Few Queries: A Hybrid Approach. Frontiers in Computer Science. 4. 5 indexed citations

11.

Berton, Gabriele, Carlo Masone, & Barbara Caputo. (2022). Rethinking Visual Geo-localization for Large-Scale Applications. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 4868–4878. 117 indexed citations

12.

Mereu, Riccardo, et al.. (2022). Learning Sequential Descriptors for Sequence-Based Visual Place Recognition. IEEE Robotics and Automation Letters. 7(4). 10383–10390. 27 indexed citations

13.

Berton, Gabriele, et al.. (2022). Deep Visual Geo-localization Benchmark. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5386–5397. 47 indexed citations

14.

Berton, Gabriele, et al.. (2021). Viewpoint Invariant Dense Matching for Visual Geolocalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 12149–12158. 25 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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