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DynamiCrafter_512
Doubiiu/DynamiCrafter_512
DynamiCrafter_512 is a machine learning model from Doubiiu. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Public
Updated Aug 1, 2024
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10.4 GB
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13
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.ckpt10.4 GB · 100%
At a glance
- Access
- Public
- Created
- Feb 3, 2024
- Updated
- Aug 1, 2024
- SHA
- 9eb87445
Model card
From the Hugging Face model README
DynamiCrafter (320x512) (text-)Image-to-Video/Image Animation Model Card
DynamiCrafter (320x512) (Text-)Image-to-Video is a video diffusion model that <br> takes in a still image as a conditioning image and text prompt describing dynamics,<br> and generates videos from it.
Model Details
Model Description
<!-- Provide a longer summary of what this model is. -->DynamiCrafter, a (Text-)Image-to-Video/Image Animation approach, aims to generate <br> short video clips (~2 seconds) from a conditioning image and text prompt.
This model was trained to generate 16 video frames at a resolution of 320x512 <br> given a context frame of the same resolution.
- Developed by: CUHK & Tencent AI Lab
- Funded by: CUHK & Tencent AI Lab
- Model type: Generative (text-)image-to-video model
- Finetuned from model: VideoCrafter1 (320x512)
Model Sources
<!-- Provide the basic links for the model. -->For research purpose, we recommend our Github repository (https://github.com/Doubiiu/DynamiCrafter), <br> which includes the detailed implementations.
- Repository: https://github.com/Doubiiu/DynamiCrafter
- Paper: https://arxiv.org/abs/2310.12190
Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->We develop this repository for RESEARCH purposes, so it can only be used for personal/research/non-commercial purposes.
Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->- The generated videos are relatively short (2 seconds, FPS=8).
- The model cannot render legible text.
- Faces and people in general may not be generated properly.
- The autoencoding part of the model is lossy, resulting in slight flickering artifacts.
How to Get Started with the Model
Check out https://github.com/Doubiiu/DynamiCrafter
- Created
- Feb 3, 2024
- Updated
- Aug 1, 2024