Luca Bertinetto

11.8k total citations · 2 hit papers
8 papers, 2.3k citations indexed

About

Luca Bertinetto is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Luca Bertinetto has authored 8 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 1 paper in Computational Mechanics. Recurrent topics in Luca Bertinetto's work include Video Surveillance and Tracking Methods (5 papers), Visual Attention and Saliency Detection (3 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Luca Bertinetto is often cited by papers focused on Video Surveillance and Tracking Methods (5 papers), Visual Attention and Saliency Detection (3 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Luca Bertinetto collaborates with scholars based in United Kingdom, China and Germany. Luca Bertinetto's co-authors include Philip H. S. Torr, Jack Valmadre, Andrea Vedaldi, Weiming Hu, João Henriques, Li Zhang, Qiang Wang, Qiang Wang, João F. Henriques and Ismail Ben Ayed and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), PubMed and Oxford University Research Archive (ORA) (University of Oxford).

In The Last Decade

Luca Bertinetto

8 papers receiving 2.2k citations

Hit Papers

End-to-end representation learning for Correlation Filter... 2017 2026 2020 2023 2017 2019 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luca Bertinetto United Kingdom 7 2.1k 558 505 245 234 8 2.3k
Goutam Bhat Sweden 4 2.0k 1.0× 692 1.2× 551 1.1× 264 1.1× 125 0.5× 9 2.2k
Peng Chu China 13 1.6k 0.8× 478 0.9× 305 0.6× 146 0.6× 263 1.1× 34 1.9k
Xiaokang Yang China 9 2.4k 1.1× 691 1.2× 574 1.1× 283 1.2× 141 0.6× 12 2.5k
Di Yuan China 22 1.3k 0.6× 529 0.9× 301 0.6× 121 0.5× 210 0.9× 56 1.6k
Luka Čehovin Zajc Slovenia 12 1.4k 0.7× 431 0.8× 318 0.6× 150 0.6× 128 0.5× 20 1.6k
Qiao Liu China 22 1.5k 0.7× 647 1.2× 318 0.6× 112 0.5× 211 0.9× 63 1.8k
Lianghua Huang China 10 1.4k 0.7× 393 0.7× 289 0.6× 151 0.6× 146 0.6× 22 1.5k
Afshin Dehghan United States 8 1.5k 0.7× 302 0.5× 196 0.4× 112 0.5× 232 1.0× 18 1.6k

Countries citing papers authored by Luca Bertinetto

Since Specialization
Citations

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

Fields of papers citing papers by Luca Bertinetto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Bertinetto

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

All Works

8 of 8 papers shown
1.
Hu, Weiming, Qiang Wang, Li Zhang, Luca Bertinetto, & Philip H. S. Torr. (2023). SiamMask: A Framework for Fast Online Object Tracking and Segmentation.. PubMed. 45(3). 3072–3089. 55 indexed citations
2.
Raue, Federico, et al.. (2022). Self-supervised Test-time Adaptation on Video Data. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2603–2612. 11 indexed citations
3.
Ayed, Ismail Ben, et al.. (2022). Parameter-free Online Test-time Adaptation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 8334–8343. 55 indexed citations
4.
Yang, Zhao, Yansong Tang, Luca Bertinetto, Hengshuang Zhao, & Philip H. S. Torr. (2021). Hierarchical Interaction Network for Video Object Segmentation from Referring Expressions. 2 indexed citations
5.
Wang, Qiang, Li Zhang, Luca Bertinetto, Weiming Hu, & Philip H. S. Torr. (2019). Fast Online Object Tracking and Segmentation: A Unifying Approach. 1328–1338. 955 indexed citations breakdown →
6.
Yang, Zhao, Qiang Wang, Luca Bertinetto, et al.. (2019). Anchor Diffusion for Unsupervised Video Object Segmentation. 931–940. 69 indexed citations
7.
Valmadre, Jack, Luca Bertinetto, João Henriques, Andrea Vedaldi, & Philip H. S. Torr. (2017). End-to-end representation learning for Correlation Filter based tracking. Oxford University Research Archive (ORA) (University of Oxford). 1029 indexed citations breakdown →
8.
Bertinetto, Luca, João F. Henriques, Jack Valmadre, Philip H. S. Torr, & Andrea Vedaldi. (2016). Learning feed-forward one-shot learners. Oxford University Research Archive (ORA) (University of Oxford). 29. 523–531. 88 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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