CCEdit: Creative and Controllable Video Editing via Diffusion Models
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.
65163b205b041d575d22b5fb
Ruoyu Feng
admin_assigned
2023-09-29T11:53:36.938Z
644101cd1a80f6d83cae6ef1
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FishNotFish
user
RuoyuFeng
65163b205b041d575d22b5fc
Wenming Weng
65163b205b041d575d22b5fd
Yanhui Wang
admin_assigned
2023-09-29T11:54:02.203Z
634fb2e9372e8a90521c4228
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yanhui wang
user
Neowyh
65163b205b041d575d22b5fe
Yuhui Yuan
admin_assigned
2023-09-29T11:54:10.890Z
646f69a6041e48e1c4728de3
https://cdn-avatars.huggingface.co/v1/production/uploads/646f69a6041e48e1c4728de3/U5OaW6PgsXTXnfG03xs9Q.png
GlyphByT5
user
GlyphByT5
65163b205b041d575d22b5ff
Jianmin Bao
admin_assigned
2023-09-29T11:54:35.688Z
6481e690f9ed842838a2b106
/avatars/e89a3c8366df504a95dc08a1a412bf3d.svg
Jianmin Bao
user
jianmin-ustc
65163b205b041d575d22b600
Chong Luo
65163b205b041d575d22b601
Zhibo Chen
65163b205b041d575d22b602
Baining Guo
CCEdit: Creative and Controllable Video Editing via Diffusion Models
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.
CCEdit is a framework that decouples video structure and appearance, utilizes ControlNet for structure preservation, and employs adaptable temporal modules and personalization techniques to enable precise and creative video editing.
ControlNet text-to-image generation DreamBooth LoRA reference-conditioned video editing key frames