Stable Video Diffusion

Stable Video Diffusion is a generative AI video model developed by Stability AI. This software allows users to create videos from images and text prompts, enabling applications such as multi-view synthesis from a single image and text-to-video generation.

Key features:
- Generative Video Capabilities: Supports video generation from images, including multi-view synthesis from a single image.
- Customizable Frame Rates: Generates videos with 14 and 25 frames at rates ranging from 3 to 30 frames per second.
- High Performance: Surpasses leading closed models in user preference studies.
- Open Source: Code available on GitHub and model weights accessible on Hugging Face.
- Adaptability: Designed for versatility across numerous downstream tasks.
- Research Focus: Intended for research purposes to gather feedback for safety and quality refinement.

How it works:
1. Users access the web-based Text-To-Video interface.
2. Text prompts are input to generate videos.
3. The model processes the input and creates corresponding video content.
4. Users can fine-tune the model on multi-view datasets for enhanced capabilities.

Integrations:
GitHub, Hugging Face

Use of AI:
Stable Video Diffusion uses generative artificial intelligence to create videos from images and text inputs. It builds upon the capabilities of the Stable Diffusion image generation model, inheriting its strengths in high-quality synthesis and task adaptability.

AI foundation model:
The model is built on the foundation of Stable Diffusion, a powerful image generation model. This allows Stable Video Diffusion to leverage advanced image synthesis capabilities for video generation.

Target users:
- Researchers in generative AI and computer vision
- Developers exploring video generation technologies
- Organizations interested in experimental video creation projects

How to access:
Stable Video Diffusion is available as an open-source project. The code can be accessed on GitHub, and model weights are available on Hugging Face. It is currently in a research preview phase, primarily intended for research and feedback collection rather than commercial use.