2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
Exploratory Unstructured Data Analysis: A Formative Study and Implications for Human-AI Collaboration
Johannes Eschner, Dominik Eitler, Max Irendorfer +3
We propose a conceptual framework for exploratory data analysis of (large) unstructured data (EluDA), combining classical elements (querying, visualization) with active knowledge c…
Scalable Class-Centric Visual Interactive Labeling
Matthias Matt, Jana Sedlakova, Jürgen Bernard +2
Large unlabeled datasets demand efficient and scalable data labeling solutions, in particular when the number of instances and classes is large. This leads to significant visual sc…
Interactive Discovery and Exploration of Visual Bias in Generative Text-to-Image Models
Johannes Eschner, Roberto Labadie-Tamayo, Matthias Zeppelzauer +1
Bias in generative Text-to-Image (T2I) models is a known issue, yet systematically analyzing such models' outputs to uncover it remains challenging. We introduce the Visual Bias Ex…
cVIL: Class-Centric Visual Interactive Labeling
Matthias Matt, Matthias Zeppelzauer, Manuela Waldner
We present cVIL, a class-centric approach to visual interactive labeling, which facilitates human annotation of large and complex image data sets. cVIL uses different property meas…