D-Index & Metrics Best Publications

Torsten Sattler

Czech Technical University in Prague
Czech Republic

Computer Science

2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 38 Citations 7,009 95 World Ranking 6411 National Ranking 10

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in Czech Republic Leader Award

Overview

What is he best known for?

The fields of study Torsten Sattler is best known for:

Operating system
Computer vision
Perception

His study on Operating system is intertwined with other disciplines of science such as Scalability and Process (computing). With his scientific publications, his incorporates both Process (computing) and Operating system. His study of Statistics brings together topics like Calibration and Matching (statistics). He integrates Calibration and Statistics in his research. Torsten Sattler links relevant scientific disciplines such as Point (geometry) and Orientation (vector space) in the realm of Geometry. Torsten Sattler performs multidisciplinary study in Point (geometry) and Geometry in his work. His work in Computer security is not limited to one particular discipline; it also encompasses Exploit and Key (lock). His Computer security research extends to the thematically linked field of Key (lock). Torsten Sattler performs multidisciplinary study on Artificial intelligence and Data mining in his works.

His most cited work include:

Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization (360 citations)
Improving Image-Based Localization by Active Correspondence Search (151 citations)
3D visual perception for self-driving cars using a multi-camera system: Calibration, mapping, localization, and obstacle detection (141 citations)

What are the main themes of his work throughout his whole career to date

Torsten Sattler links adjacent fields of study such as Image (mathematics), Pose, Ground truth and Rendering (computer graphics) in the subject of Computer vision. Artificial intelligence and Machine learning are two areas of study in which he engages in interdisciplinary work. He merges Machine learning with Artificial intelligence in his research. His work blends Statistics and Matching (statistics) studies together. While working on this project, Torsten Sattler studies both Matching (statistics) and Statistics. Linguistics is frequently linked to Feature (linguistics) in his study. His study brings together the fields of Linguistics and Feature (linguistics). Cartography is frequently linked to Scale (ratio) in his study. Torsten Sattler regularly ties together related areas like Cartography in his Scale (ratio) studies.

Torsten Sattler most often published in these fields:

Artificial intelligence (94.87%)
Computer vision (76.92%)
Pattern recognition (psychology) (38.46%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Fast image-based localization using direct 2D-to-3D matching

Torsten Sattler;Bastian Leibe;Leif Kobbelt.
international conference on computer vision (2011)

513 Citations

Image-Based Localization Using LSTMs for Structured Feature Correlation

F. Walch;C. Hazirbas;L. Leal-Taixe;T. Sattler.
international conference on computer vision (2017)

377 Citations

Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization

Torsten Sattler;Bastian Leibe;Leif Kobbelt.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2017)

369 Citations

A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos

Thomas Schops;Johannes L. Schonberger;Silvano Galliani;Torsten Sattler.
computer vision and pattern recognition (2017)

358 Citations

Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions

Torsten Sattler;Will Maddern;Carl Toft;Akihiko Torii.
computer vision and pattern recognition (2018)

352 Citations

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

Mihai Dusmanu;Ignacio Rocco;Tomas Pajdla;Marc Pollefeys.
computer vision and pattern recognition (2019)

241 Citations

Get Out of My Lab: Large-scale, Real-Time Visual-Inertial Localization

Simon Lynen;Torsten Sattler;Michael Bosse;Joel A. Hesch.
robotics science and systems (2015)

239 Citations

Improving image-based localization by active correspondence search

Torsten Sattler;Bastian Leibe;Leif Kobbelt.
european conference on computer vision (2012)

233 Citations

Comparative Evaluation of Hand-Crafted and Learned Local Features

Johannes L. Schonberger;Hans Hardmeier;Torsten Sattler;Marc Pollefeys.
computer vision and pattern recognition (2017)

229 Citations

SCRAMSAC: Improving RANSAC's efficiency with a spatial consistency filter

Torsten Sattler;Bastian Leibe;Leif Kobbelt.
international conference on computer vision (2009)

206 Citations

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Frequent Co-Authors

External Links

Personal Website for Torsten Sattler