177 citations · 519 across the 32 of their papers we have counts for
11 papers · 1 filter
MultiStar: Instance Segmentation of Overlapping Objects with Star-Convex Polygons
Florin C. Walter, Sebastian Damrich, Fred A. Hamprecht
Instance segmentation of overlapping objects in biomedical images remains a largely unsolved problem. We take up this challenge and present MultiStar, an extension to the popular i…
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks
Alberto Bailoni, Constantin Pape, Steffen Wolf +2
This work introduces a new proposal-free instance segmentation method that builds on single-instance segmentation masks predicted across the entire image in a sliding window style.…
Instance Separation Emerges from Inpainting
Steffen Wolf, Fred A. Hamprecht, Jan Funke
Deep neural networks trained to inpaint partially occluded images show a deep understanding of image composition and have even been shown to remove objects from images convincingly…
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation
Steffen Wolf, Yuyan Li, Constantin Pape +3
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label. In commonly used pipeline…
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation
Alberto Bailoni, Constantin Pape, Nathan Hütsch +4
We propose a theoretical framework that generalizes simple and fast algorithms for hierarchical agglomerative clustering to weighted graphs with both attractive and repulsive inter…
End-to-End Learned Random Walker for Seeded Image Segmentation
Lorenzo Cerrone, Alexander Zeilmann, Fred A. Hamprecht
We present an end-to-end learned algorithm for seeded segmentation. Our method is based on the Random Walker algorithm, where we predict the edge weights of the underlying graph us…