597 citations · 1.3k across the 17 of their papers we have counts for
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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…
Synthetic patches, real images: screening for centrosome aberrations in EM images of human cancer cells
Artem Lukoyanov, Isabella Haberbosch, Constantin Pape +3
Recent advances in high-throughput electron microscopy imaging enable detailed study of centrosome aberrations in cancer cells. While the image acquisition in such pipelines is aut…
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…
Leveraging Domain Knowledge to Improve Microscopy Image Segmentation with Lifted Multicuts
Constantin Pape, Alex Matskevych, Adrian Wolny +7
The throughput of electron microscopes has increased significantly in recent years, enabling detailed analysis of cell morphology and ultrastructure. Analysis of neural circuits at…
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning
Steffen Wolf, Alberto Bailoni, Constantin Pape +4
Image partitioning, or segmentation without semantics, is the task of decomposing an image into distinct segments, or equivalently to detect closed contours. Most prior work either…