@article{animeinterp2021,
  title = {Deep Animation Video Interpolation in the Wild (AnimeInterp)},
  author = {Li, S. and Zhao, S. and Yu, W. and Sun, W. and Metaxas, D. N. and Loy, C. C. and Liu, Z.},
  year = {2021},
  journal = {CVPR 2021 (IEEE/CVF)},
  url = {https://arxiv.org/abs/2104.02495},
  abstract = {Li et al. (2021) addressed the limitations of general video interpolation methods on 2D animation, where flat colours, sharp outlines and large non-linear motions cause texture-based optical flow to fail. AnimeInterp introduces a segment-guided matching module that exploits anime's region structure and a recurrent flow-refinement module for large-displacement handling, together producing accurate inbetween frames. The paper also released ATD-12K, a benchmark of 12,000 anime triplets that became the standard evaluation dataset for 2D animation interpolation. AnimeInterp is the founding domain paper for deep anime inbetweening and provides the methodological and benchmark baseline for subsequent methods including the diffusion-based ToonCrafter.},
  keywords = {video-generation, character-animation, studio-pedagogy},
  note = {AI \& Animation Education Knowledge Base}
}