CCEdit:透過擴散模型進行創意和可控的影片編輯
CCEdit: Creative and Controllable Video Editing via Diffusion Models
September 28, 2023
作者: Ruoyu Feng, Wenming Weng, Yanhui Wang, Yuhui Yuan, Jianmin Bao, Chong Luo, Zhibo Chen, Baining Guo
cs.AI
摘要
在這份工作中,我們提出了 CCEdit,這是一個多功能框架,旨在應對創意和可控制的視頻編輯挑戰。CCEdit滿足了廣泛的用戶編輯需求,通過一種創新方法解耦視頻結構和外觀,從而實現增強的創意控制。我們利用基礎的 ControlNet 架構來保持結構完整性,同時無縫集成可適應的時間模塊,與文本到圖像生成的最新個性化技術(如 DreamBooth 和 LoRA)兼容。此外,我們引入了參考條件視頻編輯,使用戶能夠通過更易管理的關鍵幀編輯過程,對視頻編輯行使精確的創意控制。我們的廣泛實驗評估證實了所提出的 CCEdit 框架的卓越功能和編輯能力。演示視頻可在以下鏈接中觀看:https://www.youtube.com/watch?v=UQw4jq-igN4。
English
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.