2 citations · 4 across the 7 of their papers we have counts for
7 papers
It's All Just Vectorization: einx, a Universal Notation for Tensor Operations
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +1
Tensor operations represent a cornerstone of modern scientific computing. However, the Numpy-like notation adopted by predominant tensor frameworks is often difficult to read and w…
Statewide Visual Geolocalization in the Wild
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +2
This work presents a method that is able to predict the geolocation of a street-view photo taken in the wild within a state-sized search region by matching against a database of ae…
C-BEV: Contrastive Bird's Eye View Training for Cross-View Image Retrieval and 3-DoF Pose Estimation
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +2
To find the geolocation of a street-view image, cross-view geolocalization (CVGL) methods typically perform image retrieval on a database of georeferenced aerial images and determi…
Geo-Tiles for Semantic Segmentation of Earth Observation Imagery
Sebastian Bullinger, Florian Fervers, Christoph Bodensteiner +1
To cope with the high requirements during the computation of semantic segmentations of earth observation imagery, current state-of-the-art pipelines divide the corresponding data i…
Uncertainty-aware Vision-based Metric Cross-view Geolocalization
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +2
This paper proposes a novel method for vision-based metric cross-view geolocalization (CVGL) that matches the camera images captured from a ground-based vehicle with an aerial imag…
Continuous Self-Localization on Aerial Images Using Visual and Lidar Sensors
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +2
This paper proposes a novel method for geo-tracking, i.e. continuous metric self-localization in outdoor environments by registering a vehicle's sensor information with aerial imag…
Improving Semantic Image Segmentation via Label Fusion in Semantically Textured Meshes
Florian Fervers, Timo Breuer, Gregor Stachowiak +3
Models for semantic segmentation require a large amount of hand-labeled training data which is costly and time-consuming to produce. For this purpose, we present a label fusion fra…