CCEdit: Creative and Controllable Video Editing via Diffusion Models

FishNotFish, Wenming Weng, yanhui wang, ART, Jianmin Bao, Chong Luo, Zhibo Chen, Baining Guo

CCEdit: Creative and Controllable Video Editing via Diffusion Models: 9 upvotes on Hugging Face Daily Papers, #16 of 16 papers on 2023-09-29. Day-by-day upvote history.

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 page on Hugging Face · arXiv

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