1.1k citations · 1.2k across the 11 of their papers we have counts for
4 papers · 1 filter
Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer +32
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…
Learning Object-Centric Video Models by Contrasting Sets
Sindy Löwe, Klaus Greff, Rico Jonschkowski +2
Contrastive, self-supervised learning of object representations recently emerged as an attractive alternative to reconstruction-based training. Prior approaches focus on contrastin…
Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks
Raghavendra Selvan, Thomas Kipf, Max Welling +4
Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-t…
Extraction of Airways using Graph Neural Networks
Raghavendra Selvan, Thomas Kipf, Max Welling +3
We present extraction of tree structures, such as airways, from image data as a graph refinement task. To this end, we propose a graph auto-encoder model that uses an encoder based…