JIA-Lab-research/Video-P2P
A text-driven video editing framework that leverages Stable Diffusion with cross-attention control for precise video modification.
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Video-P2P is a research implementation enabling text-guided video editing using diffusion models. It extends cross-attention control techniques from image editing to the video domain, allowing users to modify video content through textual prompts while preserving temporal consistency. The system builds on Stable Diffusion and incorporates techniques from prompt-to-prompt for maintaining structural integrity during editing.
Frequently asked
- What is JIA-Lab-research/Video-P2P?
- A text-driven video editing framework that leverages Stable Diffusion with cross-attention control for precise video modification.
- Is Video-P2P open source?
- Yes — JIA-Lab-research/Video-P2P is an open-source project tracked on heatdrop.
- What language is Video-P2P written in?
- JIA-Lab-research/Video-P2P is primarily written in Python.
- How popular is Video-P2P?
- JIA-Lab-research/Video-P2P has 431 stars on GitHub.
- Where can I find Video-P2P?
- JIA-Lab-research/Video-P2P is on GitHub at https://github.com/JIA-Lab-research/Video-P2P.