Analysis of Hybrid Compositions in Animation Film with Weakly Supervised Learning
<|reference_start|>Analysis of Hybrid Compositions in Animation Film with Weakly Supervised Learning: 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.<|reference_end|>
@article{portos2024analysis,
    title={Analysis of Hybrid Compositions in Animation Film with Weakly Supervised
  Learning},
    author={M'onica Apellaniz Portos, Roberto Labadie-Tamayo, Claudius Stemmler,
  Erwin Feyersinger, Andreas Babic, Franziska Bruckner, Vr"a"ath "Ohner and
  Matthias Zeppelzauer},
    journal={arXiv preprint arXiv:2410.04789},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.04789},
    primaryClass={cs.CV cs.AI}
}