14 citations · 24 across the 5 of their papers we have counts for
4 papers · 1 filter
Multi-label Learning with Missing Values using Combined Facial Action Unit Datasets
Jaspar Pahl, Ines Rieger, Dominik Seuss
Facial action units allow an objective, standardized description of facial micro movements which can be used to describe emotions in human faces. Annotating data for action units i…
Unique Class Group Based Multi-Label Balancing Optimizer for Action Unit Detection
Ines Rieger, Jaspar Pahl, Dominik Seuss
Balancing methods for single-label data cannot be applied to multi-label problems as they would also resample the samples with high occurrences. We propose to reformulate this prob…
Verifying Deep Learning-based Decisions for Facial Expression Recognition
Ines Rieger, Rene Kollmann, Bettina Finzel +2
Neural networks with high performance can still be biased towards non-relevant features. However, reliability and robustness is especially important for high-risk fields such as cl…
Multi-Label Class Balancing Algorithm for Action Unit Detection
Jaspar Pahl, Ines Rieger, Dominik Seuss
Isolated facial movements, so-called Action Units, can describe combined emotions or physical states such as pain. As datasets are limited and mostly imbalanced, we present an appr…