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vdo/stable-video-diffusion-img2vid
stable-video-diffusion-img2vid is a machine learning model from vdo. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.
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Updated Nov 22, 2023
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From the Hugging Face model README
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.
(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.
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).
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
The model is intended for research purposes only. Possible research areas and tasks include
Excluded uses are described below.
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.
The model is intended for research purposes only.