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Found 8 papers, 2 papers with code
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label.
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks
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.
Accurate and versatile 3D segmentation of plant tissues at cellular resolution
Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs.
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label.
DISCo: Deep learning, Instance Segmentation, and Correlations for cell segmentation in calcium imaging
In order to use the data gained with calcium imaging, it is necessary to extract individual cells and their activity from the recordings.
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation
We propose a theoretical framework that generalizes simple and fast algorithms for hierarchical agglomerative clustering to weighted graphs with both attractive and repulsive interactions between the nodes.
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning
Unlike seeded watershed, the algorithm can accommodate not only attractive but also repulsive cues, allowing it to find a previously unspecified number of segments without the need for explicit seeds or a tunable threshold.
The Mutex Watershed: Efficient, Parameter-Free Image Partitioning
Image partitioning, or segmentation without semantics, is the task of decomposing an image into distinct segments; or equivalently, the task of detecting closed contours in an image.
