@article{tooncrafter2024,
  title = {ToonCrafter: Generative Cartoon Interpolation},
  year = {2024},
  journal = {SIGGRAPH Asia 2024},
  url = {https://dl.acm.org/doi/abs/10.1145/3687761},
  abstract = {ToonCrafter, published at SIGGRAPH Asia 2024, addresses the in-betweening problem in drawn animation by adapting live-action video diffusion priors to the drawn image domain through a technique called toon rectification learning. Given two cartoon keyframes, the model generates plausible intermediate frames including content not visible in either keyframe, filling the gap generatively. The paper is open-sourced with public weights, making it directly deployable in teaching labs. It matches the scope contract's exemplar class of SIGGRAPH papers on neural in-betweening.},
  keywords = {generative-ai, video-generation, character-animation, motion-synthesis, production-practice},
  note = {AI \& Animation Education Knowledge Base}
}