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20182025
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cs.CV2025

Scaling Image Geo-Localization to Continent Level

Philipp Lindenberger, Paul-Edouard Sarlin, Jan Hosang +4

Determining the precise geographic location of an image at a global scale remains an unsolved challenge. Standard image retrieval techniques are inefficient due to the sheer volume…

cs.CV2021

Efficient Large Scale Inlier Voting for Geometric Vision Problems

Dror Aiger, Simon Lynen, Jan Hosang +1

Outlier rejection and equivalently inlier set optimization is a key ingredient in numerous applications in computer vision such as filtering point-matches in camera pose estimation…

cs.CV2019

SuperNCN: Neighbourhood consensus network for robust outdoor scenes matching

Grzegorz Kurzejamski, Jacek Komorowski, Lukasz Dabala +3

In this paper, we present a framework for computing dense keypoint correspondences between images under strong scene appearance changes. Traditional methods, based on nearest neigh…

cs.CV2019

Large-scale, real-time visual-inertial localization revisited

Simon Lynen, Bernhard Zeisl, Dror Aiger +5

The overarching goals in image-based localization are scale, robustness and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both do…

cs.CV2018

SConE: Siamese Constellation Embedding Descriptor for Image Matching

Tomasz Trzcinski, Jacek Komorowski, Lukasz Dabala +3

Numerous computer vision applications rely on local feature descriptors, such as SIFT, SURF or FREAK, for image matching. Although their local character makes image matching proces…

cs.CV2018

Interest point detectors stability evaluation on ApolloScape dataset

Jacek Komorowski, Konrad Czarnota, Tomasz Trzcinski +2

In the recent years, a number of novel, deep-learning based, interest point detectors, such as LIFT, DELF, Superpoint or LF-Net was proposed. However there's a lack of a standard b…