1 citations · 1 across the 3 of their papers we have counts for
6 papers
3D Masked Autoencoders are Robust Learners of Volumetric and Multimodal Cellular Representations for Microscopy
Amirhossein Kardoost, Lion Gleiter, Tingying Peng +1
Self-supervised learning in fluorescence microscopy often relies on 2D projections, despite the inherently three-dimensional nature of cells. We present a systematic comparison of…
HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopy
Julius Riel, Vishwa Mohan Singh, Sai Anirudh Aryasomayajula +10
Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups. In biological cell images, current self-supervised lea…
Optimizing Edge Detection for Image Segmentation with Multicut Penalties
Steffen Jung, Sebastian Ziegler, Amirhossein Kardoost +1
The Minimum Cost Multicut Problem (MP) is a popular way for obtaining a graph decomposition by optimizing binary edge labels over edge costs. While the formulation of a MP from ind…
Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation
Amirhossein Kardoost, Margret Keuper
The minimum cost lifted multicut approach has proven practically good performance in a wide range of applications such as image decomposition, mesh segmentation, multiple object tr…
Self-supervised Sparse to Dense Motion Segmentation
Amirhossein Kardoost, Kalun Ho, Peter Ochs +1
Observable motion in videos can give rise to the definition of objects moving with respect to the scene. The task of segmenting such moving objects is referred to as motion segment…
Object Segmentation Tracking from Generic Video Cues
Amirhossein Kardoost, Sabine Müller, Joachim Weickert +1
We propose a light-weight variational framework for online tracking of object segmentations in videos based on optical flow and image boundaries. While high-end computer vision met…