no code implementations • ICCV 2021 • Ara Jafarzadeh, Manuel Lopez Antequera, Pau Gargallo, Yubin Kuang, Carl Toft, Fredrik Kahl, Torsten Sattler
Visual localization is the problem of estimating the position and orientation from which a given image (or a sequence of images) is taken in a known scene.
1 code implementation • CVPR 2021 • Paul-Edouard Sarlin, Ajaykumar Unagar, Måns Larsson, Hugo Germain, Carl Toft, Viktor Larsson, Marc Pollefeys, Vincent Lepetit, Lars Hammarstrand, Fredrik Kahl, Torsten Sattler
In this paper, we go Back to the Feature: we argue that deep networks should focus on learning robust and invariant visual features, while the geometric estimation should be left to principled algorithms.
no code implementations • 1 Jan 2021 • Carl Toft, Georg Bökman, Fredrik Kahl
In this work, we analyze linear operators from $L^2(S^2) \rightarrow L^2(S^2)$ which are equivariant to azimuthal rotations, that is, rotations around the z-axis.
1 code implementation • 21 Aug 2020 • Carl Toft, Daniyar Turmukhambetov, Torsten Sattler, Fredrik Kahl, Gabriel Brostow
Good local features improve the robustness of many 3D re-localization and multi-view reconstruction pipelines.
1 code implementation • 18 Aug 2019 • Måns Larsson, Erik Stenborg, Carl Toft, Lars Hammarstrand, Torsten Sattler, Fredrik Kahl
In this paper, we propose a new neural network, the Fine-Grained Segmentation Network (FGSN), that can be used to provide image segmentations with a larger number of labels and can be trained in a self-supervised fashion.
no code implementations • ECCV 2018 • Carl Toft, Erik Stenborg, Lars Hammarstrand, Lucas Brynte, Marc Pollefeys, Torsten Sattler, Fredrik Kahl
Robust and accurate visual localization across large appearance variations due to changes in time of day, seasons, or changes of the environment is a challenging problem which is of importance to application areas such as navigation of autonomous robots.
no code implementations • 16 Jan 2018 • Erik Stenborg, Carl Toft, Lars Hammarstrand
Robust cross-seasonal localization is one of the major challenges in long-term visual navigation of autonomous vehicles.
2 code implementations • CVPR 2018 • Torsten Sattler, Will Maddern, Carl Toft, Akihiko Torii, Lars Hammarstrand, Erik Stenborg, Daniel Safari, Masatoshi Okutomi, Marc Pollefeys, Josef Sivic, Fredrik Kahl, Tomas Pajdla
Visual localization enables autonomous vehicles to navigate in their surroundings and augmented reality applications to link virtual to real worlds.