Davide Moltisanti
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Human-Computer Interaction top 10%
- Control and Systems Engineering
- Signal Processing
- Co-authors
- Giovanni Maria FarinellaMichael WrayDima DamenEvangelos KazakosWill PriceToby PerrettJonathan MunroAntonino Furnari
- Topics
- 3D Surveying and Cultural Heritage (3 papers)Multimodal Machine Learning Applications (3 papers)Video Analysis and Summarization (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionMeasurement
- Partner nations
- ItalyUnited KingdomNetherlands
In The Last Decade
Davide Moltisanti
7 papers receiving 307 citations
Hit Papers
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 265
- Artificial Intelligence 137
- Human-Computer Interaction 25
- Control and Systems Engineering 23
- Signal Processing 23
Countries citing papers authored by Davide Moltisanti
This map shows the geographic impact of Davide Moltisanti'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 Moltisanti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Davide Moltisanti more than expected).
Fields of papers citing papers by Davide Moltisanti
This network shows the impact of papers produced by Davide Moltisanti. 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 Moltisanti. The network helps show where Davide Moltisanti may publish in the future.
Co-authorship network of co-authors of Davide Moltisanti
This figure shows the co-authorship network connecting the top 25 collaborators of Davide Moltisanti. A scholar is included among the top collaborators of Davide Moltisanti 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 Davide Moltisanti. Davide Moltisanti 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 | 2 | |
| 3 | Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100breakdown → | 188 |
| 4 | 104 | |
| 5 | 0 | |
| 6 | 11 | |
| 7 | 14 | |
| 8 | 1 |
About Davide Moltisanti
Davide Moltisanti is a scholar working on Geology, Computer Vision and Pattern Recognition and Ocean Engineering, having authored 8 papers that have together received 322 indexed citations. Recurring topics across this work include 3D Surveying and Cultural Heritage (3 papers), Multimodal Machine Learning Applications (3 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (265 citations), Human-Computer Interaction (25 citations) and Artificial Intelligence (137 citations). Davide Moltisanti has collaborated with scholars based in Italy, United Kingdom and Netherlands. Frequent co-authors include Giovanni Maria Farinella, Michael Wray, Dima Damen, Evangelos Kazakos, Will Price, Toby Perrett, Jonathan Munro, Antonino Furnari, Hazel Doughty and Jian Ma. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Measurement.
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.