Search Results for author: Carl Toft

Found 8 papers, 4 papers with code

CrowdDriven: A New Challenging Dataset for Outdoor Visual Localization

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.

Benchmarking Self-Driving Cars +1

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

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.

Camera Localization Metric Learning +1

Azimuthal Rotational Equivariance in Spherical CNNs

no code implementations1 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.

Single-Image Depth Prediction Makes Feature Matching Easier

1 code implementation21 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.

Depth Estimation Depth Prediction

Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization

1 code implementation18 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.

Autonomous Driving Visual Localization

Semantic Match Consistency for Long-Term Visual Localization

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.

Visual Localization

Long-term Visual Localization using Semantically Segmented Images

no code implementations16 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.

Autonomous Vehicles Semantic Segmentation +2

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