Fabian Caba Heilbron
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- Multimodal Machine Learning Applications 12
- Video Analysis and Summarization 11
- Human Pose and Action Recognition 11
- Advanced Image and Video Retrieval Techniques 6
- Generative Adversarial Networks and Image Synthesis 3
- Artificial Intelligence top 1%
- Anomaly Detection Techniques and Applications 6
- Domain Adaptation and Few-Shot Learning 4
- Human-Computer Interaction top 5%
- Signal Processing top 5%
- Music and Audio Processing 3
- Co-authors
- Bernard GhanemJuan Carlos NieblesVíctor EscorciaOliver WangFederico PerazziStan SclaroffKate SaenkoPing Hu
- Journals
- IEEE Access (1 paper)IEEE Robotics and Automation Letters (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2 papers)
- Partner nations
- United StatesSaudi ArabiaCanada
In The Last Decade
Fabian Caba Heilbron
24 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 1.8k
- Artificial Intelligence 993
- Human-Computer Interaction 78
- Signal Processing 111
- Biomedical Engineering 176
Countries citing papers authored by Fabian Caba Heilbron
This map shows the geographic impact of Fabian Caba Heilbron'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 Fabian Caba Heilbron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabian Caba Heilbron more than expected).
Fields of papers citing papers by Fabian Caba Heilbron
This network shows the impact of papers produced by Fabian Caba Heilbron. 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 Fabian Caba Heilbron. The network helps show where Fabian Caba Heilbron may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabian Caba Heilbron, 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 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 5 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 26 | |
| 11 | 2022 | 18 | |
| 12 | 2022 | 45 | |
| 13 | 2022 | 5 | |
| 14 | 2019 | 6 | |
| 15 | Action Search: Learning to Search for Human Activities in Untrimmed Videos | 2017 | 3 |
| 16 | 2017 | 59 | |
| 17 | 2016 | 162 | |
| 18 | ActivityNet: A large-scale video benchmark for human activity understandingbreakdown → | 2015 | 1435 |
| 19 | 2015 | 26 | |
| 20 | 2014 | 22 |
About Fabian Caba Heilbron
Fabian Caba Heilbron is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 25 papers that have together received 2.0k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (12 papers), Video Analysis and Summarization (11 papers), Human Pose and Action Recognition (11 papers), Advanced Image and Video Retrieval Techniques (6 papers), Anomaly Detection Techniques and Applications (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Music and Audio Processing (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.8k citations), Artificial Intelligence (993 citations) and Human-Computer Interaction (78 citations). Fabian Caba Heilbron has collaborated with scholars based in United States, Saudi Arabia and Canada. Frequent co-authors include Bernard Ghanem, Juan Carlos Niebles, Víctor Escorcia, Oliver Wang, Federico Perazzi, Stan Sclaroff, Kate Saenko, Ping Hu, Zhe Lin and Ali Thabet. Their work appears in journals such as IEEE Access, IEEE Robotics and Automation Letters and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.