Neil Alldrin
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Computer Graphics and Computer-Aided Design top 1%
- Computational Mechanics top 10%
- Media Technology top 5%
- Co-authors
- Ivan KrasinTom DuerigVittorio FerrariAlina KuznetsovaJasper UijlingsShahab KamaliJordi Pont-TusetStefan Popov
- Topics
- Advanced Neural Network Applications (5 papers)Multimodal Machine Learning Applications (4 papers)Computer Graphics and Visualization Techniques (4 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- International Journal of Computer VisionDigital Access to Scholarship at Harvard (DASH) (Harvard University)arXiv (Cornell University)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Neil Alldrin
11 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Computer Vision and Pattern Recognition 1.5k
- Artificial Intelligence 815
- Computer Graphics and Computer-Aided Design 266
- Computational Mechanics 117
- Media Technology 102
Countries citing papers authored by Neil Alldrin
This map shows the geographic impact of Neil Alldrin'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 Neil Alldrin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil Alldrin more than expected).
Fields of papers citing papers by Neil Alldrin
This network shows the impact of papers produced by Neil Alldrin. 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 Neil Alldrin. The network helps show where Neil Alldrin may publish in the future.
Co-authorship network of co-authors of Neil Alldrin
This figure shows the co-authorship network connecting the top 25 collaborators of Neil Alldrin. A scholar is included among the top collaborators of Neil Alldrin 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 Neil Alldrin. Neil Alldrin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 130 | |
| 4 | The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scalebreakdown → | 960 |
| 5 | The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scalebreakdown → | 378 |
| 6 | 264 | |
| 7 | 168 | |
| 8 | 52 | |
| 9 | 78 | |
| 10 | 8 | |
| 11 | 14 |
About Neil Alldrin
Neil Alldrin is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 11 papers that have together received 2.1k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Multimodal Machine Learning Applications (4 papers) and Computer Graphics and Visualization Techniques (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (266 citations), Computer Vision and Pattern Recognition (1.5k citations) and Artificial Intelligence (815 citations). Neil Alldrin has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Ivan Krasin, Tom Duerig, Vittorio Ferrari, Alina Kuznetsova, Jasper Uijlings, Shahab Kamali, Jordi Pont-Tuset, Stefan Popov, Alexander Kolesnikov and David Kriegman. Their work appears in journals such as International Journal of Computer Vision, Digital Access to Scholarship at Harvard (DASH) (Harvard University) and arXiv (Cornell University).
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.