52 citations · 75 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
DISCo: Deep learning, Instance Segmentation, and Correlations for cell segmentation in calcium imaging
Elke Kirschbaum, Alberto Bailoni, Fred A. Hamprecht
Calcium imaging is one of the most important tools in neurophysiology as it enables the observation of neuronal activity for hundreds of cells in parallel and at single-cell resolu…
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…
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…