Matthias Dantone
- Computer Vision and Pattern Recognition top 1%
- Human-Computer Interaction top 2%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Co-authors
- Luc Van GoolJüergen GallGabriele FanelliAndrea FossatiGiulia FanelliChristian LeistnerLukas BossardTill Quack
- Topics
- Face recognition and analysis (5 papers)Video Surveillance and Tracking Methods (5 papers)Human Pose and Action Recognition (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionLirias (KU Leuven)
- Partner nations
- SwitzerlandBelgiumGermany
In The Last Decade
Matthias Dantone
8 papers receiving 837 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 777
- Human-Computer Interaction 145
- Signal Processing 115
- Artificial Intelligence 103
- Biomedical Engineering 61
Countries citing papers authored by Matthias Dantone
This map shows the geographic impact of Matthias Dantone'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 Matthias Dantone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Dantone more than expected).
Fields of papers citing papers by Matthias Dantone
This network shows the impact of papers produced by Matthias Dantone. 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 Matthias Dantone. The network helps show where Matthias Dantone may publish in the future.
Co-authorship network of co-authors of Matthias Dantone
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Dantone. A scholar is included among the top collaborators of Matthias Dantone 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 Matthias Dantone. Matthias Dantone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 44 | |
| 3 | 168 | |
| 4 | 38 | |
| 5 | Random Forests for Real Time 3D Face Analysisbreakdown → | 367 |
| 6 | 241 | |
| 7 | 18 | |
| 8 | Multimedia Event Detection (MED) Evaluation Task. | 2 |
About Matthias Dantone
Matthias Dantone is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Industrial and Manufacturing Engineering, having authored 8 papers that have together received 880 indexed citations. Recurring topics across this work include Face recognition and analysis (5 papers), Video Surveillance and Tracking Methods (5 papers) and Human Pose and Action Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (777 citations), Human-Computer Interaction (145 citations) and Signal Processing (115 citations). Matthias Dantone has collaborated with scholars based in Switzerland, Belgium and Germany. Frequent co-authors include Luc Van Gool, Jüergen Gall, Gabriele Fanelli, Andrea Fossati, Giulia Fanelli, Christian Leistner, Lukas Bossard, Till Quack, Rasmus Rothe and Jelena Tešić. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Lirias (KU Leuven).
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.