Generate short videos from an initial image or text using Stable Video Diffusion, a latent video diffusion model.
Stable Video Diffusion is an advanced generative AI video model developed by Stability AI that allows users to generate videos from images and text. This pioneering tool is currently in a research preview and is designed to elevate content creation by transforming static inputs into dynamic, engaging video content. Whether for media, education, marketing, or entertainment, Stable Video Diffusion expands creative horizons and enhances storytelling capabilities.
To get started with Stable Video Diffusion, simply upload an image or text input through the user-friendly interface. Once uploaded, the AI model processes your input and generates a visually stunning short video clip, typically around four seconds in length. This innovative tool allows for quick experimentation and iteration in content creation.
Stable Video offers flexible subscription plans tailored to fit various budgets and needs. Users can explore different plans to find what best suits their video creation requirements, ensuring that everyone has the chance to utilize this cutting-edge technology.
Stable Video Diffusion is an AI model that generates videos from images or text, designed for various applications in content creation.
The model supports three aspect ratios: 16:9, 9:16, and 1:1, allowing for versatile video generation.
While generally no strict limits exist, very large files may impact processing time and performance, so it's wise to keep file sizes manageable.
Currently, the model is optimized for short video clips, around four seconds long, with potential for longer videos in the future.
It signifies a breakthrough in AI-driven video generation, offering new content creation possibilities across various sectors.
It is one of the few open-source models known for high-quality output and its flexibility in various applications, making it highly accessible.
Yes, the code for Stable Video Diffusion is available on GitHub, promoting collaboration and further development in the open-source community.
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