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arXiv · 2410.04789

Analysis of Hybrid Compositions in Animation Film with Weakly Supervised Learning

Mónica Apellaniz Portos·Roberto Labadie-Tamayo·Claudius Stemmler·Erwin Feyersinger·Andreas Babic·Franziska Bruckner·Vrääth Öhner·Matthias Zeppelzauer
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Abstract

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.

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Mónica Apellaniz Portos, Roberto Labadie-Tamayo, Claudius Stemmler, Erwin Feyersinger, Andreas Babic, Franziska Bruckner, Vrääth Öhner, Matthias Zeppelzauer. 2024-10-07. Analysis of Hybrid Compositions in Animation Film with Weakly Supervised Learning. https://arxiv.org/abs/2410.04789

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