2 papers
cs.HC2025
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…
cs.HC2024
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…