Patrick Poirson
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Natural Language Processing Techniques
Papers in
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- Human Pose and Action Recognition 1
- Advanced Vision and Imaging 1
- Generative Adversarial Networks and Image Synthesis 1
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- Advanced Graph Neural Networks 1
- Natural Language Processing Techniques 1
- Co-authors
- Alexander C. Berg (2 shared papers)Licheng Yu (1 shared paper)Tamara L. Berg (1 shared paper)Shan Yang (1 shared paper)Eunbyung Park (1 shared paper)Jana Košecká (1 shared paper)Abhinav Shrivastava (1 shared paper)Pengxiang Wu (1 shared paper)
- Journals
- Lecture notes in computer science (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United States
In The Last Decade
Patrick Poirson
4 papers receiving 774 citations
Patrick Poirson's Hit Papers
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 691
- Artificial Intelligence 452
- Aerospace Engineering 56
- Human-Computer Interaction 13
- Geology 9
Countries citing papers authored by Patrick Poirson
This map shows the geographic impact of Patrick Poirson'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 Patrick Poirson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Poirson more than expected).
Fields of papers citing papers by Patrick Poirson
This network shows the impact of papers produced by Patrick Poirson. 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 Patrick Poirson. The network helps show where Patrick Poirson may publish in the future.
Co-authors
The 11 scholars most cited alongside Patrick Poirson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Modeling Context in Referring Expressions Hit paper breakdown → | 2016 | 650 |
| 2 | 2017 | 109 | |
| 3 | 2023 | 26 | |
| 4 | 2022 | 7 |
About Patrick Poirson
Patrick Poirson is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Information Systems and Aerospace Engineering, having authored 4 papers that have together received 792 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (1 paper), Robotics and Sensor-Based Localization (1 paper), Caching and Content Delivery (1 paper), Advanced Graph Neural Networks (1 paper), Natural Language Processing Techniques (1 paper), Advanced Vision and Imaging (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Recommender Systems and Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (691 citations), Artificial Intelligence (452 citations), Aerospace Engineering (56 citations), Human-Computer Interaction (13 citations) and Geology (9 citations). Patrick Poirson has collaborated with scholars based in United States. Frequent co-authors include Alexander C. Berg, Licheng Yu, Tamara L. Berg, Shan Yang, Eunbyung Park, Jana Košecká, Abhinav Shrivastava, Pengxiang Wu, Hanyu Wang and Chen Wang. Their work appears in journals such as Lecture notes in computer science 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.