title: AnimateDiff-Lightning: Cross-Model Diffusion Distillation
summary: We present AnimateDiff-Lightning for lightning-fast video generation. Our
  model uses progressive adversarial diffusion distillation to achieve new
  state-of-the-art in few-step video generation. We discuss our modifications to
  adapt it for the video modality. Furthermore, we propose to simultaneously
  distill the probability flow of multiple base diffusion models, resulting in a
  single distilled motion module with broader style compatibility. We are pleased
  to release our distilled AnimateDiff-Lightning model for the community's use.
paper_authors._id: 65fa41407fcb33a703f37eeb
paper_authors.name: Shanchuan Lin
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-03-21T08:27:51.111Z
paper_authors._id: 645863f7dc18eb1a9b5d29df
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/645863f7dc18eb1a9b5d29df/t49Nnyl4tbkUn7CmQqKZh.jpeg
paper_authors.fullname: Peter Lin
paper_authors.type: user
paper_authors.user: PeterL1n
paper_authors._id: 65fa41407fcb33a703f37eec
paper_authors.name: Xiao Yang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-07-03T07:42:09.552Z
paper_authors._id: 62b3d2490385d6048985b42b
paper_authors.avatarUrl: /avatars/1c4e534d086d53ef1057fbc00334350a.svg
paper_authors.fullname: Xiao Yang
paper_authors.type: user
paper_authors.user: seravee008
paper_title: AnimateDiff-Lightning: Cross-Model Diffusion Distillation
paper_summary: We present AnimateDiff-Lightning for lightning-fast video generation. Our
  model uses progressive adversarial diffusion distillation to achieve new
  state-of-the-art in few-step video generation. We discuss our modifications to
  adapt it for the video modality. Furthermore, we propose to simultaneously
  distill the probability flow of multiple base diffusion models, resulting in a
  single distilled motion module with broader style compatibility. We are pleased
  to release our distilled AnimateDiff-Lightning model for the community's use.
paper_ai_keywords: progressive adversarial diffusion distillation few accuracy video generation diffusion models state-of-the-art video modality distilled motion module style compatibility AnimateDiff-Lightning semi-supervised learning probability flow distilled AnimateDiff-Lightning