34 citations · 56 across the 5 of their papers we have counts for
6 papers
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…
Intrinsic timescales of spiking activity in humans during wakefulness and sleep
Annika Hagemann, Marcel Stephan Kehl, Jonas Dehning +5
Information processing in the brain requires integration of information over time. Such an integration can be achieved if signals are maintained in the network activity for the req…
Modeling dynamic target deformation in camera calibration
Annika Hagemann, Moritz Knorr, Christoph Stiller
Most approaches to camera calibration rely on calibration targets of well-known geometry. During data acquisition, calibration target and camera system are typically moved w.r.t. e…
Inferring bias and uncertainty in camera calibration
Annika Hagemann, Moritz Knorr, Holger Janssen +1
Accurate camera calibration is a precondition for many computer vision applications. Calibration errors, such as wrong model assumptions or imprecise parameter estimation, can dete…
MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity
F. P. Spitzner, J. Dehning, J. Wilting +4
Here we present our Python toolbox "MR. Estimator" to reliably estimate the intrinsic timescale from electrophysiologal recordings of heavily subsampled systems. Originally intende…
Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex
Annika Hagemann, Jens Wilting, Bita Samimizad +2
Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-f…