title: CCEdit: Creative and Controllable Video Editing via Diffusion Models
summary: In this work, we present CCEdit, a versatile framework designed to address
  the challenges of creative and controllable video editing. CCEdit accommodates
  a wide spectrum of user editing requirements and enables enhanced creative
  control through an innovative approach that decouples video structure and
  appearance. We leverage the foundational ControlNet architecture to preserve
  structural integrity, while seamlessly integrating adaptable temporal modules
  compatible with state-of-the-art personalization techniques for text-to-image
  generation, such as DreamBooth and LoRA.Furthermore, we introduce
  reference-conditioned video editing, empowering users to exercise precise
  creative control over video editing through the more manageable process of
  editing key frames. Our extensive experimental evaluations confirm the
  exceptional functionality and editing capabilities of the proposed CCEdit
  framework. Demo video is available at
  https://www.youtube.com/watch?v=UQw4jq-igN4.
paper_authors._id: 65163b205b041d575d22b5fb
paper_authors.name: Ruoyu Feng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-29T11:53:36.938Z
paper_authors._id: 644101cd1a80f6d83cae6ef1
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paper_authors.fullname: FishNotFish
paper_authors.type: user
paper_authors.user: RuoyuFeng
paper_authors._id: 65163b205b041d575d22b5fc
paper_authors.name: Wenming Weng
paper_authors._id: 65163b205b041d575d22b5fd
paper_authors.name: Yanhui Wang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-29T11:54:02.203Z
paper_authors._id: 634fb2e9372e8a90521c4228
paper_authors.avatarUrl: /avatars/42a5f79bcca67bd000ac08db685b8b0a.svg
paper_authors.fullname: yanhui wang
paper_authors.type: user
paper_authors.user: Neowyh
paper_authors._id: 65163b205b041d575d22b5fe
paper_authors.name: Yuhui Yuan
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-29T11:54:10.890Z
paper_authors._id: 646f69a6041e48e1c4728de3
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paper_authors.fullname: GlyphByT5
paper_authors.type: user
paper_authors.user: GlyphByT5
paper_authors._id: 65163b205b041d575d22b5ff
paper_authors.name: Jianmin Bao
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-29T11:54:35.688Z
paper_authors._id: 6481e690f9ed842838a2b106
paper_authors.avatarUrl: /avatars/e89a3c8366df504a95dc08a1a412bf3d.svg
paper_authors.fullname: Jianmin Bao
paper_authors.type: user
paper_authors.user: jianmin-ustc
paper_authors._id: 65163b205b041d575d22b600
paper_authors.name: Chong Luo
paper_authors._id: 65163b205b041d575d22b601
paper_authors.name: Zhibo Chen
paper_authors._id: 65163b205b041d575d22b602
paper_authors.name: Baining Guo
paper_title: CCEdit: Creative and Controllable Video Editing via Diffusion Models
paper_summary: In this work, we present CCEdit, a versatile framework designed to address
  the challenges of creative and controllable video editing. CCEdit accommodates
  a wide spectrum of user editing requirements and enables enhanced creative
  control through an innovative approach that decouples video structure and
  appearance. We leverage the foundational ControlNet architecture to preserve
  structural integrity, while seamlessly integrating adaptable temporal modules
  compatible with state-of-the-art personalization techniques for text-to-image
  generation, such as DreamBooth and LoRA.Furthermore, we introduce
  reference-conditioned video editing, empowering users to exercise precise
  creative control over video editing through the more manageable process of
  editing key frames. Our extensive experimental evaluations confirm the
  exceptional functionality and editing capabilities of the proposed CCEdit
  framework. Demo video is available at
  https://www.youtube.com/watch?v=UQw4jq-igN4.
paper_ai_keywords: ControlNet architecture adaptable temporal modules text-to-image generation DreamBooth LoRA reference-conditioned video editing key frames