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Stable Video Diffusion Image-to-Video Model Card
Stable Video Diffusion (SVD) Image-to-Video is a diffusion model that takes in a still image as a conditioning frame, and generates a video from it.
Model Details
Model Description
(SVD) Image-to-Video is a latent diffusion model trained to generate short video clips from an image conditioning. This model was trained to generate 14 frames at resolution 576x1024 given a context frame of the same size. We also finetune the widely used f8-decoder for temporal consistency. For convenience, we additionally provide the model with the standard frame-wise decoder here.
- Developed by: Stability AI
- Funded by: Stability AI
- Model type: Generative image-to-video model
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
Evaluation
The chart above evaluates user preference for SVD-Image-to-Video over GEN-2 and PikaLabs.
SVD-Image-to-Video is preferred by human voters in terms of video quality. For details on the user study, we refer to the research paper
Uses
Inference
git clone [email protected]:Stability-AI/generative-models.git
cd generative-models
pip install -r ./requirements/pt2.txt
Download this model card
git lfs install
git clone https://huggingface.co/stabilityai/stable-video-diffusion-img2vid
PYTHONPATH=. streamlit run scripts/demo/video_sampling.py --server.port <port-id>
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.
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.