3 citations · 7 across the 4 of their papers we have counts for
4 papers · 1 filter
XRefine: Attention-Guided Keypoint Match Refinement
Jan Fabian Schmid, Annika Hagemann
Sparse keypoint matching is crucial for 3D vision tasks, yet current keypoint detectors often produce spatially inaccurate matches. Existing refinement methods mitigate this issue…
Deep Metric Learning for Ground Images
Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz +1
Ground texture based localization methods are potential prospects for low-cost, high-accuracy self-localization solutions for robots. These methods estimate the pose of a given que…
Model-Based Parameter Optimization for Ground Texture Based Localization Methods
Jan Fabian Schmid, Stephan F. Simon, Rudolf Mester
A promising approach to accurate positioning of robots is ground texture based localization. It is based on the observation that visual features of ground images enable fingerprint…
Features for Ground Texture Based Localization -- A Survey
Jan Fabian Schmid, Stephan F. Simon, Rudolf Mester
Ground texture based vehicle localization using feature-based methods is a promising approach to achieve infrastructure-free high-accuracy localization. In this paper, we provide t…