David Ferstl
Impact in
- Media Technology top 1%
- Image Processing Techniques and Applications
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- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Optical measurement and interference techniques
- Image Enhancement Techniques
- Advanced Neural Network Applications
Papers in
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- Advanced Vision and Imaging 7
- Optical measurement and interference techniques 6
- Human Pose and Action Recognition 3
- Advanced Image Processing Techniques 2
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- Robotics and Sensor-Based Localization 8
- Co-authors
- Horst Bischof (11 shared papers)Christian Reinbacher (3 shared papers)René Ranftl (2 shared papers)Matthias Rüther (9 shared papers)Íñigo Alonso (1 shared paper)Ana C. Murillo (1 shared paper)Luis Montesano (1 shared paper)Gernot Riegler (4 shared papers)
- Journals
- Lecture notes in computer science (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
In The Last Decade
David Ferstl
15 papers receiving 781 citations
David Ferstl's Hit Papers
Peers
Comparison fields: 5 of 57
- Media Technology 364
- Computer Vision and Pattern Recognition 720
- Instrumentation 30
- Artificial Intelligence 130
- Geology 18
Countries citing papers authored by David Ferstl
This map shows the geographic impact of David Ferstl'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 David Ferstl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Ferstl more than expected).
Fields of papers citing papers by David Ferstl
This network shows the impact of papers produced by David Ferstl. 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 David Ferstl. The network helps show where David Ferstl may publish in the future.
Co-authors
The 17 scholars most cited alongside David Ferstl, 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 | Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation Hit paper breakdown → | 2013 | 403 |
| 2 | Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank Hit paper breakdown → | 2021 | 195 |
| 3 | 2015 | 69 | |
| 4 | 2016 | 67 | |
| 5 | 2015 | 17 | |
| 6 | 2014 | 10 | |
| 7 | 2023 | 8 | |
| 8 | 2016 | 7 | |
| 9 | 2015 | 7 | |
| 10 | 2014 | 5 | |
| 11 | 2012 | 2 | |
| 12 | 2013 | 2 | |
| 13 | 2025 | 1 | |
| 14 | Integral Shape from Focus | 2012 | 1 |
| 15 | 2012 | 1 |
About David Ferstl
David Ferstl is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Media Technology, Control and Systems Engineering and Instrumentation, having authored 15 papers that have together received 795 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (8 papers), Advanced Vision and Imaging (7 papers), Optical measurement and interference techniques (6 papers), Image Processing Techniques and Applications (4 papers), Human Pose and Action Recognition (3 papers), Hand Gesture Recognition Systems (2 papers), Advanced Optical Sensing Technologies (2 papers) and Advanced Image Processing Techniques (2 papers). The work is most often cited by research in Media Technology (364 citations), Computer Vision and Pattern Recognition (720 citations), Instrumentation (30 citations), Artificial Intelligence (130 citations) and Geology (18 citations). David Ferstl has collaborated with scholars based in Austria, Germany and China. Frequent co-authors include Horst Bischof, Christian Reinbacher, René Ranftl, Matthias Rüther, Íñigo Alonso, Ana C. Murillo, Luis Montesano, Gernot Riegler, Piotr Skrzypczyński and Michał Nowicki. Their work appears in journals such as Lecture notes in computer science, Proceedings of the AAAI Conference on Artificial Intelligence and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.