The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. - Steffen Wolf 001; Constantin Pape; Alberto Bailoni; Nasim Rahaman; Anna Kreshuk; Ullrich Köthe; Fred A. Hamprecht (ECCV (4), 2018)

The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning. - Steffen Wolf 001; Alberto Bailoni; Constantin Pape; Nasim Rahaman; Anna Kreshuk; Ullrich Köthe; Fred A. Hamprecht (CoRR, 2019)

A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation. - Alberto Bailoni; Constantin Pape; Steffen Wolf 001; Thorsten Beier; Anna Kreshuk; Fred A. Hamprecht (CoRR, 2019)

DISCo for the CIA: Deep learning, Instance Segmentation, and Correlations for Calcium Imaging Analysis. - Elke Kirschbaum; Alberto Bailoni; Fred A. Hamprecht (CoRR, 2019)

Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks. - Alberto Bailoni; Constantin Pape; Steffen Wolf 001; Anna Kreshuk; Fred A. Hamprecht (GCPR, 2020)

The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation. - Steffen Wolf 001; Yuyan Li; Constantin Pape; Alberto Bailoni; Anna Kreshuk; Fred A. Hamprecht (ECCV (6), 2020)

DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging. - Elke Kirschbaum; Alberto Bailoni; Fred A. Hamprecht (MICCAI (5), 2020)

The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning. - Steffen Wolf 001; Alberto Bailoni; Constantin Pape; Nasim Rahaman; Anna Kreshuk; Ullrich Köthe; Fred A. Hamprecht (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Deep Learning for Graph-Based Image Instance Segmentation. - Alberto Bailoni (2021)

GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation. - Alberto Bailoni; Constantin Pape; Nathan Hütsch; Steffen Wolf 001; Thorsten Beier; Anna Kreshuk; Fred A. Hamprecht (CVPR, 2022)