Torsten Sattler
Impact in
- Computer Vision and Pattern Recognition top 0.05%
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Optical measurement and interference techniques
- Geology top 0.1%
- 3D Surveying and Cultural Heritage
Papers in
-
- Advanced Vision and Imaging 61
- Advanced Image and Video Retrieval Techniques 56
- Advanced Neural Network Applications 10
- Optical measurement and interference techniques 10
- Multimodal Machine Learning Applications 9
-
- Robotics and Sensor-Based Localization 86
- Co-authors
- Marc Pollefeys (56 shared papers)Leif P. Kobbelt (11 shared papers)Bastian Leibe (8 shared papers)Andreas Geiger (10 shared papers)Tomáš Pajdla (11 shared papers)Josef Šivic (9 shared papers)Akihiko Torii (9 shared papers)Thomas Schöps (6 shared papers)
- Journals
- Lecture notes in computer science (50 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (5 papers)International Journal of Computer Vision (3 papers)ACM Transactions on Graphics (1 paper)Advances in computer vision and pattern recognition (1 paper)
- Partner nations
- SwitzerlandCzechiaSweden
In The Last Decade
Torsten Sattler
125 papers receiving 9.1k citations
Torsten Sattler's Hit Papers
Peers
Comparison fields: 5 of 123
- Computer Vision and Pattern Recognition 7.7k
- Geology 1.5k
- Aerospace Engineering 6.2k
- Computer Graphics and Computer-Aided Design 284
- Media Technology 430
Countries citing papers authored by Torsten Sattler
This map shows the geographic impact of Torsten Sattler'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 Torsten Sattler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Torsten Sattler more than expected).
Fields of papers citing papers by Torsten Sattler
This network shows the impact of papers produced by Torsten Sattler. 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 Torsten Sattler. The network helps show where Torsten Sattler may publish in the future.
Co-authors
The 25 scholars most cited alongside Torsten Sattler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 144 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | D2-Net: A Trainable CNN for Joint Description and Detection of Local Features Hit paper breakdown → | 2019 | 867 |
| 2 | A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos Hit paper breakdown → | 2017 | 630 |
| 3 | Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions Hit paper breakdown → | 2018 | 514 |
| 4 | Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization Hit paper breakdown → | 2016 | 428 |
| 5 | Image-Based Localization Using LSTMs for Structured Feature Correlation Hit paper breakdown → | 2017 | 383 |
| 6 | Fast image-based localization using direct 2D-to-3D matching Hit paper breakdown → | 2011 | 366 |
| 7 | InLoc: Indoor Visual Localization with Dense Matching and View Synthesis Hit paper breakdown → | 2018 | 342 |
| 8 | Understanding the Limitations of CNN-Based Absolute Camera Pose Regression Hit paper breakdown → | 2019 | 317 |
| 9 | BAD SLAM: Bundle Adjusted Direct RGB-D SLAM Hit paper breakdown → | 2019 | 278 |
| 10 | Mip-Splatting: Alias-Free 3D Gaussian Splatting Hit paper breakdown → | 2024 | 272 |
| 11 | Computer Vision and Pattern Recognition 2020 Hit paper breakdown → | 2021 | 252 |
| 12 | 2017 | 240 | |
| 13 | 2012 | 234 | |
| 14 | 2012 | 190 | |
| 15 | 2015 | 190 | |
| 16 | 2017 | 173 | |
| 17 | 2021 | 170 | |
| 18 | 2014 | 151 | |
| 19 | 2020 | 135 | |
| 20 | 2017 | 134 |
About Torsten Sattler
Torsten Sattler is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Geology, Computer Graphics and Computer-Aided Design and Environmental Engineering, having authored 144 papers that have together received 9.3k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (86 papers), Advanced Vision and Imaging (61 papers), Advanced Image and Video Retrieval Techniques (56 papers), 3D Surveying and Cultural Heritage (26 papers), Advanced Neural Network Applications (10 papers), Optical measurement and interference techniques (10 papers), Multimodal Machine Learning Applications (9 papers) and Computer Graphics and Visualization Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (7.7k citations), Geology (1.5k citations), Aerospace Engineering (6.2k citations), Computer Graphics and Computer-Aided Design (284 citations) and Media Technology (430 citations). Torsten Sattler has collaborated with scholars based in Switzerland, Czechia and Sweden. Frequent co-authors include Marc Pollefeys, Leif P. Kobbelt, Bastian Leibe, Andreas Geiger, Tomáš Pajdla, Josef Šivic, Akihiko Torii, Thomas Schöps, Laura Leal-Taixé and Johannes L. Schönberger. Their work appears in journals such as Lecture notes in computer science, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, ACM Transactions on Graphics and Advances in computer vision and pattern recognition.
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.