Meta unveils Emu Video and Emu Edit
Generative AI has emerged as a transformative force, empowering individuals to create and express themselves in novel and imaginative ways.
Today, significant milestones have been achieved in generative AI research with the unveiling of Emu Video and Emu Edit.
What is Emu Video?
Emu Video presents a game-changing approach to text-to-video generation based on diffusion models. By factorizing the video generation process into two steps – generating images conditioned on text prompts and then generating videos conditioned on both text and images – this method has created a more efficient and effective process. Unlike prior methods requiring multiple models, Emu Video uses just two diffusion models to generate high-resolution (512x512) four-second-long videos at 16 frames per second.
Human evaluations have shown remarkable results, with Meta's video generations outperforming prior work by a significant margin. In fact, Meta's model was preferred over Make-A-Video by 96% of respondents in terms of quality and 85% in terms of faithfulness to the text prompt.
Additionally, the same model can "animate" user-provided images based on a text prompt, further highlighting its versatility.
Here are some of the key features of Emu Video:
- Unified architecture for video generation tasks
- Supports text-only, image-only, and combined text-and-image inputs
- Factorized approach to video generation enables efficient training
- State-of-the-art performance in human evaluations
- Can animate user-provided images
You may check the Emu Video paper to learn more about how it works.
What is Emu Edit?
Emu Edit offers precise control over image editing tasks through recognition and generation techniques. Unlike traditional image manipulation methods that often result in over-modification or under-performance, Emu Edit precisely follows instructions, ensuring that only relevant pixels are altered. This means that when adding text to a baseball cap, the cap itself remains unchanged.
Meta's key insight is integrating computer vision tasks as instructions to image generation models, offering unprecedented control in image generation and editing. We've developed a large dataset of synthesized samples (10 million) to train Meta's model, resulting in superior edit results in terms of instruction accuracy and image quality.
In Meta's evaluations, Emu Edit demonstrated state-of-the-art performance for a range of image editing tasks, outperforming current methods.
Here are some of the key features of Emu Edit:
- Free-form editing through instructions
- Precise pixel alteration
- Unprecedented control with computer vision tasks
- Exceptional editing results
- State-of-the-art performance
Users can read the Emu Edit paper to learn more about the latest generation model from Meta.
An undeniable potential
While this research is still in its fundamental stages, the potential use cases are abundant. Imagine generating animated stickers or GIFs on the fly, editing photos and images with ease, animating static posts for Instagram, or creating entirely new content.
Read also: Meta double downs on AI integration.
These technologies have the potential to empower individuals to express themselves in new ways – from ideating on a new concept to livening up a social media post.Advertisement