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Funded Projects:

DeToL – Deep Topology Learning - funded by the BMBF (Federal Ministry of Education and Research)

Video Segmentation from Multiple Representations using Lifted Multicuts - DFG Project KE 2264/1-1

more details coming soon ...

 

Recent Projects on Robustness:

Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space

 

Image Generation:

Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation

Spectral Distribution aware Image Generation

Watch your up-convolution: Cnn based generative deep neural networks are failing to reproduce spectral distributions

 

Neural Architecture Search:

in the context of DeToL – Deep Topology Learning - funded by the BMBF (Federal Ministry of Education and Research)

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search

NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search

Neural Architecture Performance Prediction Using Graph Neural Networks

 

Motion Segmentation and Tracking:

Motion Segmentation & Multiple Object Tracking by Correlation Co-Clustering

Motion trajectory segmentation via minimum cost multicuts

Object Segmentation Tracking from Generic Video Cues

A Two-Stage Minimum Cost Multicut Approach to Self-Supervised Multiple Person Tracking

Self-supervised Sparse to Dense Motion Segmentation

Motion Segmentation & Multiple Object Tracking by Correlation  Co-Clustering | Max Planck Institute for Intelligent Systems

Projects on Efficient Image Decompsition:

Solving Minimum Cost Lifted Multicuts By Node Agglomeration

Efficient Decomposition of Image and Mesh Graphs by Lifted Multicuts

A Benders Decomposition Approach to Correlation Clustering