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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 into hybrid compositions in animation film.

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Analysis of Hybrid Compositions in Animation Film with Weakly Supervised Learning

  • 会议论文

  • 发表日期：

    2025年

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

摘要

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 into hybrid compositions in animation film.