Ingo Fruend
Impact in
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- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Video Analysis and Summarization
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
Papers in
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- Visual perception and processing mechanisms 4
- Neural dynamics and brain function 3
- Face Recognition and Perception 1
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- Digital Media Forensic Detection 1
- Generative Adversarial Networks and Image Synthesis 1
- Multimodal Machine Learning Applications 1
- Co-authors
- Ingo Bax (1 shared paper)P.N. Yianilos (1 shared paper)Raghav Goyal (1 shared paper)Samira Ebrahimi Kahou (1 shared paper)Roland Memisevic (1 shared paper)Christian Thurau (1 shared paper)Joanna Materzyńska (1 shared paper)Heuna Kim (1 shared paper)
- Partner nations
- CanadaIranUnited Kingdom
In The Last Decade
Ingo Fruend
6 papers receiving 779 citations
Ingo Fruend's Hit Papers
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 728
- Artificial Intelligence 432
- Human-Computer Interaction 66
- Biomedical Engineering 139
- Endocrinology, Diabetes and Metabolism 43
Countries citing papers authored by Ingo Fruend
This map shows the geographic impact of Ingo Fruend'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 Ingo Fruend with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ingo Fruend more than expected).
Fields of papers citing papers by Ingo Fruend
This network shows the impact of papers produced by Ingo Fruend. 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 Ingo Fruend. The network helps show where Ingo Fruend may publish in the future.
Co-authors
The 14 scholars most cited alongside Ingo Fruend, 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 | The “Something Something” Video Database for Learning and Evaluating Visual Common Sense Hit paper breakdown → | 2017 | 772 |
| 2 | 2018 | 9 | |
| 3 | 2018 | 7 | |
| 4 | 2018 | 6 | |
| 5 | 2018 | 4 | |
| 6 | 2020 | 1 |
About Ingo Fruend
Ingo Fruend is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Cellular and Molecular Neuroscience, Social Psychology and Atomic and Molecular Physics, and Optics, having authored 6 papers that have together received 799 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (4 papers), Neural dynamics and brain function (3 papers), Neurobiology and Insect Physiology Research (1 paper), Cell Image Analysis Techniques (1 paper), Digital Media Forensic Detection (1 paper), Face Recognition and Perception (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (728 citations), Artificial Intelligence (432 citations), Human-Computer Interaction (66 citations), Biomedical Engineering (139 citations) and Endocrinology, Diabetes and Metabolism (43 citations). Ingo Fruend has collaborated with scholars based in Canada, Iran and United Kingdom. Frequent co-authors include Ingo Bax, P.N. Yianilos, Raghav Goyal, Samira Ebrahimi Kahou, Roland Memisevic, Christian Thurau, Joanna Materzyńska, Heuna Kim, Vincent Michalski and Florian Hoppe. Their work appears in journals such as Journal of Vision and Vision Research.
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.