Öhner, Vrääth
Analysis of Hybrid Compositions in Animation Film with Weakly Supervised Learning
Portos, Mónica Apellaniz, Labadie-Tamayo, Roberto, Stemmler, Claudius, Feyersinger, Erwin, Babic, Andreas, Bruckner, Franziska, Öhner, Vrääth, Zeppelzauer, Matthias
We present an approach for the analysis of hybrid visual compositions in animation in the domain of ephemeral film. We combine ideas from semi-supervised and weakly supervised learning to train a model that can segment hybrid compositions without requiring pre-labeled segmentation masks. We evaluate our approach on a set of ephemeral films from 13 film archives. Results demonstrate that the proposed learning strategy yields a performance close to a fully supervised baseline. On a qualitative level the performed analysis provides interesting insights on hybrid compositions in animation film.