text2video-zero-openjourney
Maintainer: wcarle
13
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | View on Arxiv |
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Model overview
The text2video-zero-openjourney model, developed by Picsart AI Research, is a groundbreaking AI model that enables zero-shot video generation using text prompts. It leverages the power of existing text-to-image synthesis methods, such as Stable Diffusion, and adapts them for the video domain. This innovative approach allows users to generate dynamic, temporally consistent videos directly from textual descriptions, without the need for additional training on video data.
Model inputs and outputs
The text2video-zero-openjourney model takes in a text prompt as input and generates a video as output. The model can also be conditioned on additional inputs, such as poses or edges, to guide the video generation process.
Inputs
- Prompt: A textual description of the desired video content, such as "A panda is playing guitar on Times Square".
- Pose Guidance: An optional input in the form of a video containing poses that can be used to guide the video generation.
- Edge Guidance: An optional input in the form of a video containing edge information that can be used to guide the video generation.
- Dreambooth Specialization: An optional input in the form of a Dreambooth-trained model, which can be used to generate videos with a specific style or character.
Outputs
- Video: The generated video, which follows the provided textual prompt and any additional guidance inputs.
Capabilities
The text2video-zero-openjourney model is capable of generating a wide variety of dynamic video content, ranging from animals performing actions to fantastical scenes with anthropomorphized characters. For example, the model can generate videos of "A horse galloping on a street", "An astronaut dancing in outer space", or "A panda surfing on a wakeboard".
What can I use it for?
The text2video-zero-openjourney model opens up exciting possibilities for content creation and storytelling. Creators and artists can use this model to quickly generate unique video content for various applications, such as social media, animation, and filmmaking. Businesses can leverage the model to create dynamic, personalized video advertisements or product demonstrations. Educators and researchers can explore the model's capabilities for educational content and data visualization.
Things to try
One interesting aspect of the text2video-zero-openjourney model is its ability to incorporate additional guidance inputs, such as poses and edges. By providing these inputs, users can further influence the generated videos and achieve specific visual styles or narratives. For example, users can generate videos of "An alien dancing under a flying saucer" by providing a video of dancing poses as guidance.
Another fascinating capability of the model is its integration with Dreambooth specialization. By fine-tuning the model with a Dreambooth-trained model, users can generate videos with a distinct visual style or character, such as "A GTA-5 man" or "An Arcane-style character".
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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