Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions

@article{Sattler2018Benchmarking6O,
  title={Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions},
  author={Torsten Sattler and William P. Maddern and Carl Toft and Akihiko Torii and Lars Hammarstrand and Erik Stenborg and Daniel Safari and M. Okutomi and Marc Pollefeys and Josef Sivic and Fredrik Kahl and Tom{\'a}s Pajdla},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={8601-8610}
}
Visual localization enables autonomous vehicles to navigate in their surroundings and augmented reality applications to link virtual to real worlds. Practical visual localization approaches need to be robust to a wide variety of viewing condition, including day-night changes, as well as weather and seasonal variations, while providing highly accurate 6 degree-of-freedom (6DOF) camera pose estimates. In this paper, we introduce the first benchmark datasets specifically designed for analyzing the… 
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