Stable Video Diffusion Img2vid Xt 1 1

🚀 Stable Video Diffusion 1.1 Image-to-Video Model Card

Stable Video Diffusion (SVD) 1.1 Image-to-Video is a diffusion model. It takes a still image as a conditioning frame and generates a video from it, which is useful for various research and creative applications.

🚀 Quick Start

Check out https://github.com/Stability-AI/generative-models

✨ Features

• Image - to - Video Generation: Takes a still image as input and generates a short video clip.
• Fine - Tuned Performance: Fine - tuned from SVD Image - to - Video [25 frames] to improve output consistency.

📦 Installation

No specific installation steps are provided in the original README.

💻 Usage Examples

No code examples are provided in the original README.

📚 Documentation

Model Details

Model Description

(SVD 1.1) Image - to - Video is a latent diffusion model trained to generate short video clips from an image conditioning. This model was trained to generate 25 frames at a resolution of 1024x576 given a context frame of the same size, finetuned from SVD Image - to - Video [25 frames].

Fine tuning was performed with fixed conditioning at 6FPS and Motion Bucket Id 127 to improve the consistency of outputs without the need to adjust hyperparameters. These conditions are still adjustable and have not been removed. Performance outside of the fixed conditioning settings may vary compared to SVD 1.0.

Model Sources

For research purposes, we recommend our generative - models Github repository (https://github.com/Stability - AI/generative - models), which implements the most popular diffusion frameworks (both training and inference).

• Repository: https://github.com/Stability - AI/generative - models
• Paper: https://stability.ai/research/stable - video - diffusion - scaling - latent - video - diffusion - models - to - large - datasets

Uses

Direct Use

The model is intended for research purposes only. Possible research areas and tasks include:

• Research on generative models.
• Safe deployment of models which have the potential to generate harmful content.
• Probing and understanding the limitations and biases of generative models.
• Generation of artworks and use in design and other artistic processes.
• Applications in educational or creative tools.

Excluded uses are described below.

Out - of - Scope Use

The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out - of - scope for the abilities of this model. The model should not be used in any way that violates Stability AI's [Acceptable Use Policy](https://stability.ai/use - policy).

Limitations and Bias

Limitations

• The generated videos are rather short (<= 4sec), and the model does not achieve perfect photorealism.
• The model may generate videos without motion, or very slow camera pans.
• The model cannot be controlled through text.
• The model cannot render legible text.
• Faces and people in general may not be generated properly.
• The autoencoding part of the model is lossy.

Recommendations

The model is intended for research purposes only.

🔧 Technical Details

The fine - tuning of the model was performed with fixed conditioning at 6FPS and Motion Bucket Id 127 to enhance output consistency without hyperparameter adjustment. However, these conditions can still be modified. The performance may vary outside of the fixed conditioning settings compared to SVD 1.0.

📄 License

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