10 citations · 14 across the 6 of their papers we have counts for
6 papers
Unsupervised Semantic Segmentation Facilitates Model Understanding
Xiaoyan Yu, Lisa Mais, Jannik Franzen +4
Self-supervised learning (SSL) has produced a diverse landscape of vision transformers (ViTs) whose pretrained representations support a wide range of downstream tasks. Towards a b…
Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images
Rajalakshmi Palaniappan, Christoph Karg, Nemesio Navarro-Arambula +4
Blood vessel segmentation and -tracing are essential tasks in many medical imaging applications. Although numerous methods exist, the prevailing segment-then-fix paradigm is fundam…
FISBe: A real-world benchmark dataset for instance segmentation of long-range thin filamentous structures
Lisa Mais, Peter Hirsch, Claire Managan +6
Instance segmentation of neurons in volumetric light microscopy images of nervous systems enables groundbreaking research in neuroscience by facilitating joint functional and morph…
How Shift Equivariance Impacts Metric Learning for Instance Segmentation
Josef Lorenz Rumberger, Xiaoyan Yu, Peter Hirsch +6
Metric learning has received conflicting assessments concerning its suitability for solving instance segmentation tasks. It has been dismissed as theoretically flawed due to the sh…
Probabilistic Deep Learning for Instance Segmentation
Josef Lorenz Rumberger, Lisa Mais, Dagmar Kainmueller
Probabilistic convolutional neural networks, which predict distributions of predictions instead of point estimates, led to recent advances in many areas of computer vision, from im…
PatchPerPix for Instance Segmentation
Peter Hirsch, Lisa Mais, Dagmar Kainmueller
We present a novel method for proposal free instance segmentation that can handle sophisticated object shapes which span large parts of an image and form dense object clusters with…