About
Emu Video employs a unique approach to text-to-video generation by using diffusion models to factorize the process into two distinct steps: first, by generating an image based on a text prompt and then creating a video conditioned on both the prompt and the generated image. This method allows for the efficient training of high-quality video generation models without relying on a deep cascade of models. Specifically, Emu Video can produce 512px, 4-second long videos at 16fps using only two diffusion models, offering superior results compared to existing models like Make-a-Video and Imagen-Video. This system has been evaluated with human raters who confirmed its state-of-the-art quality and faithfulness to input prompts.
Competitive Advantage
Employs a simple two-step generation process that efficiently creates state-of-the-art quality videos from text inputs.
Use Cases
Pros
- Efficient model training
- High-quality video output
- Simple two-step process
- Superior prompt faithfulness
Cons
- Limited to 4-second videos
- Fixed video resolution
- Restricted to 16fps
- Specific to text prompts
Tags
Pricing
Features and Benefits
Two-Step Generation Process
Utilizes a process of first creating an image and then a video, conditioned on a text prompt, to ensure high-quality results.
Efficient Use of Diffusion Models
Harnesses two diffusion models to generate videos, making it more resource-efficient than deep cascade models.
State-of-the-Art Quality
Produces videos that outperform existing models in terms of quality and fidelity to prompts.
Target Audience
Frequently Asked Questions
Emu Video uses diffusion models to generate videos from text prompts.
The videos are 4 seconds long.
The videos are produced at 512px resolution.
By using a two-step process involving image and video conditioning on prompts.
The research was conducted by a team at Meta.
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