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Computer Science

D-Index
51
Citations
8726
World Ranking
5411
National Ranking
28

Overview

Fredrik Kahl is affiliated with Chalmers University of Technology in Sweden. Their research primarily focuses on areas within Computer Science and Engineering, with a strong emphasis on Computer Vision and Pattern Recognition, Artificial Intelligence, and Aerospace Engineering among other related fields.

Their work spans several main topics, including:

  • Robotics and Sensor-Based Localization
  • Advanced Vision and Imaging
  • Advanced Image and Video Retrieval Techniques
  • Machine Learning and Data Classification
  • Anomaly Detection Techniques and Applications
  • Image Retrieval and Classification Techniques
  • Domain Adaptation and Few-Shot Learning

Fredrik Kahl has published extensively in various venues, with recurring publications found in:

  • arXiv (Cornell University)
  • 2022 26th International Conference on Pattern Recognition (ICPR)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Among their recent papers are:

  • Long-Term Visual Localization Revisited, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • A case for using rotation invariant features in state of the art feature matchers, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision, 2022, 2022 26th International Conference on Pattern Recognition (ICPR)
  • CrowdDriven: A New Challenging Dataset for Outdoor Visual Localization, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Development of a novel method to measure bone marrow fat fraction in older women using high-resolution peripheral quantitative computed tomography, 2022, Osteoporosis International

Frequent collaborators include:

  • Georg Bökman
  • Lennart Svensson
  • Torsten Sattler
  • Lars Hammarstrand
  • Carl Toft

Best Publications

  • Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions

    Torsten Sattler;Will Maddern;Carl Toft;Akihiko Torii

  • Multiple-View Geometry Under the {$L_\infty$}-Norm

    F. Kahl;R. Hartley

  • A minimal solution for relative pose with unknown focal length

    Henrik Stewénius;David Nistér;Fredrik Kahl;Frederik Schaffalitzky

  • Global Optimization through Rotation Space Search

    Richard I. Hartley;Fredrik Kahl

  • Globally Optimal Estimates for Geometric Reconstruction Problems

    Fredrik Kahl;Didier Henrion

  • Real-Time Camera Tracking and 3D Reconstruction Using Signed Distance Functions

    Erik Bylow;Jürgen Sturm;Christian Kerl;Fredrik Kahl

  • City-Scale Localization for Cameras with Known Vertical Direction

    Linus Svarm;Olof Enqvist;Fredrik Kahl;Magnus Oskarsson

  • Back to the Feature: Learning Robust Camera Localization from Pixels to Pose

    Paul-Edouard Sarlin;Ajaykumar Unagar;Mans Larsson;Hugo Germain

  • Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks

    Oscar Jimenez-del-Toro;Henning Muller;Markus Krenn;Katharina Gruenberg

  • Semantic Match Consistency for Long-Term Visual Localization

    Carl Toft;Erik Stenborg;Lars Hammarstrand;Lucas Brynte

  • Branch-and-Bound Methods for Euclidean Registration Problems

    C. Olsson;F. Kahl;M. Oskarsson

  • Normalized Cuts Revisited: A Reformulation for Segmentation with Linear Grouping Constraints

    Anders Eriksson;Carl Olsson;Fredrik Kahl

  • Long-Term Visual Localization Revisited.

    Carl Toft;Will Maddern;Akihiko Torii;Lars Hammarstrand

  • Non-sequential structure from motion

    Olof Enqvist;Fredrik Kahl;Carl Olsson

  • Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction

    Anurag Arnab;Shuai Zheng;Sadeep Jayasumana;Bernardino Romera-Paredes

  • Practical Global Optimization for Multiview Geometry

    Fredrik Kahl;Sameer Agarwal;Manmohan Krishna Chandraker;David Kriegman

  • Optimal algorithms in multiview geometry

    Richard Hartley;Fredrik Kahl

  • Optimal correspondences from pairwise constraints

    Olof Enqvist;Klas Josephson;Fredrik Kahl

  • Curvature regularity for region-based image segmentation and inpainting: A linear programming relaxation

    Thomas Schoenemann;Fredrik Kahl;Daniel Cremers

  • Parallel and distributed graph cuts by dual decomposition

    Petter Strandmark;Fredrik Kahl

  • 2009 IEEE 12th International Conference on Computer Vision (ICCV)

    Stephen Gould;Richard Fulton;Daphne Koller;Ido Leichter

Frequent Co-Authors

Anders Heyden
Anders Heyden Lund University
Richard Hartley
Richard Hartley Australian National University
Karl Johan Åström
Karl Johan Åström Lund University
Daniel Cremers
Daniel Cremers Technical University of Munich
Torsten Sattler
Torsten Sattler Czech Technical University in Prague
Philip H. S. Torr
Philip H. S. Torr University of Oxford
Yuri Boykov
Yuri Boykov University of Waterloo
Manmohan Chandraker
Manmohan Chandraker University of California, San Diego
Victor Lempitsky
Victor Lempitsky Samsung (South Korea)
David J. Kriegman
David J. Kriegman University of California, San Diego

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