Stable Video Diffusion

Advanced AI model that transforms static images into high-resolution, dynamic videos. Try it out now!

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How to Use Stable Video Diffusion

Getting started with Stable Video Diffusion is easy. Follow these simple steps to create your own AI-generated videos:

  1. Select Your Image: Choose an image that you want to transform into a video.
  2. Define Video Parameters: Customize the video settings such as frame rate and length according to your preference.
  3. Generate Your Video: Let our AI do the magic and transform your image into a dynamic video.
  4. Download and Share: Download your generated video and share your creation with the world.

Explore Creations with Stable Video Diffusion

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Frequently Asked Questions

Stable Video Diffusion is an advanced AI model developed for generative video creation. It transforms static images into high-resolution, dynamic videos using state-of-the-art text-to-video and image-to-video generation techniques.

Stable Video Diffusion uses latent video diffusion models, incorporating temporal layers and finetuning on video datasets. It's based on the principles of transforming and manipulating visual data, allowing it to generate video content from images.

Key features include high-resolution video generation, customizable frame rates (between 3 and 30 frames per second), and the ability to generate up to 25 frames. It's adaptable for various video applications, including multi-view synthesis from a single image.

Currently, Stable Video Diffusion is released for research purposes only and is not intended for real-world or commercial applications. It is primarily a tool for exploring the capabilities and potential of AI in video generation.

The code and model weights for Stable Video Diffusion are available on our GitHub repository and Hugging Face page. Users can also sign up for a waitlist to access a new web experience featuring a Text-To-Video interface.

While Stable Video Diffusion is a powerful tool, it has some limitations such as generating relatively short videos (less than 4 seconds), limited camera motion capabilities, and challenges in generating legible text and faces accurately.