Constantin Pape

Orcid: 0000-0001-6562-7187

Affiliations:

University of Göttingen, Germany
EMBL Heidelberg, Germany (former)

According to our database¹, Constantin Pape authored at least 20 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Other

Bibliography

2024

ViM-UNet: Vision Mamba for Biomedical Segmentation.

[BibT_eX]

[DOI]

Anwai Archit

Constantin Pape

CoRR, 2024

2023

Current Progress and Challenges in Large-Scale 3D Mitochondria Instance Segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, December, 2023

Probabilistic Domain Adaptation for Biomedical Image Segmentation.

[BibT_eX]

[DOI]

Anwai Archit

Constantin Pape

CoRR, 2023

Reinforcement learning for instance segmentation with high-level priors.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

From Shallow to Deep: Exploiting Feature-Based Classifiers for Domain Adaptation in Semantic Segmentation.

[BibT_eX]

[DOI]

Frontiers Comput. Sci., 2022

Sparse Object-level Supervision for Instance Segmentation with Pixel Embeddings.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Scalable Instance Segmentation for Microscopy

[BibT_eX]

[DOI]

Constantin Pape

PhD thesis, 2021

The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Stateless actor-critic for instance segmentation with high-level priors.

[BibT_eX]

[DOI]

CoRR, 2021

2020

The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020

2019

Leveraging Domain Knowledge to Improve Microscopy Image Segmentation With Lifted Multicuts.

[BibT_eX]

[DOI]

Frontiers Comput. Sci., 2019

A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation.

[BibT_eX]

[DOI]

CoRR, 2019

Leveraging Domain Knowledge to improve EM image segmentation with Lifted Multicuts.

[BibT_eX]

[DOI]

CoRR, 2019

The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning.

[BibT_eX]

[DOI]

CoRR, 2019

Synthetic Patches, Real Images: Screening for Centrosome Aberrations in EM Images of Human Cancer Cells.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018

Synaptic Cleft Segmentation in Non-isotropic Volume Electron Microscopy of the Complete Drosophila Brain.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

The Mutex Watershed: Efficient, Parameter-Free Image Partitioning.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Solving Large Multicut Problems for Connectomics via Domain Decomposition.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Constantin Pape

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