AI is happening. The future is updating.stable-video-diffusion-img2vid-xt
(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 25 frames at resolution 576x1024 given a context frame of the same size, finetuned from [SVD Image-to-Video [14 frames]](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid). 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 - **Finetuned from model:** SVD Image-to-Video [14 frames] 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).
(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 25 frames at resolution 576x1024 given a context frame of the same size, finetuned from [SVD Image-to-Video [14 frames]](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid). 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 - **Finetuned from model:** SVD Image-to-Video [14 frames] 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).