5 citations · 7 across the 6 of their papers we have counts for
7 papers
Structural Limits of the Information-Theoretic Uncertainty Decomposition
Jakob Lønborg Christensen, Christian F. Baumgartner, Morten Rieger Hannemose +2
Uncertainty estimation in machine learning typically decomposes uncertainty into aleatoric uncertainty (AU) and epistemic uncertainty (EU) using the standard information-theoretic…
Rethinking Uncertainty Quantification and Entanglement in Image Segmentation
Jakob Lønborg Christensen, Vedrana Andersen Dahl, Morten Rieger Hannemose +2
Uncertainty quantification (UQ) is crucial in safety-critical applications such as medical image segmentation. Total uncertainty is typically decomposed into data-related aleatoric…
Towards Agnostic and Holistic Universal Image Segmentation with Bit Diffusion
Jakob Lønborg Christensen, Morten Rieger Hannemose, Anders Bjorholm Dahl +1
This paper introduces a diffusion-based framework for universal image segmentation, making agnostic segmentation possible without depending on mask-based frameworks and instead pre…
Diffusion Based Ambiguous Image Segmentation
Jakob Lønborg Christensen, Morten Rieger Hannemose, Anders Bjorholm Dahl +1
Medical image segmentation often involves inherent uncertainty due to variations in expert annotations. Capturing this uncertainty is an important goal and previous works have used…
Two Views Are Better than One: Monocular 3D Pose Estimation with Multiview Consistency
Christian Keilstrup Ingwersen, Rasmus Tirsgaard, Rasmus Nylander +3
Deducing a 3D human pose from a single 2D image is inherently challenging because multiple 3D poses can correspond to the same 2D representation. 3D data can resolve this pose ambi…
SportsPose -- A Dynamic 3D sports pose dataset
Christian Keilstrup Ingwersen, Christian Mikkelstrup, Janus Nørtoft Jensen +2
Accurate 3D human pose estimation is essential for sports analytics, coaching, and injury prevention. However, existing datasets for monocular pose estimation do not adequately cap…
Superaccurate Camera Calibration via Inverse Rendering
Morten Hannemose, Jakob Wilm, Jeppe Revall Frisvad
The most prevalent routine for camera calibration is based on the detection of well-defined feature points on a purpose-made calibration artifact. These could be checkerboard saddl…