![Alibaba Open Sources EMO: Make Your Avatar Videos Sing Naturally Alibaba Open Sources EMO: Make Your Avatar Videos Sing Naturally](https://i2.wp.com/miro.medium.com/v2/resize:fit:2003/0*rhEnMylmbHCMs94k.png?w=1920&resize=1920,1106&ssl=1)
Alibaba Open Sources EMO: Make Your Avatar Videos Sing Naturally
Last Updated on February 29, 2024 by Editorial Team
Author(s): Meng Li
Originally published on Towards AI.
https://humanaigc.github.io/emote-portrait-alive/
For us, generating a single 2D image with technologies like Stable Diffusion or Midjourney is no longer a challenge.
However, the complexity arises when we attempt to stitch these consecutively generated 2D images together to create a smooth video.
In the realm of 3D generation technology, avatar technology has always been a focal point.
This technology can be broadly divided into two main directions: creation and animation of digital avatars.
Today, we’re delving into a new advancement in the animation of digital avatars.
Recently, Alibaba has open-sourced a project named EMO: Emote Portrait Alive.
Traditionally, avatar videos generated appear stiff and unnatural, resembling a simple compilation of static facial expressions.
However, the advent of EMO technology has changed this narrative.
EMO has successfully produced singing avatar videos, achieving a natural and lively effect.
So, how does EMO technology accomplish this?
And what is the quality of the avatar videos it generates?
Let’s explore together.
https://humanaigc.github.io/emote-portrait-alive/
To create lifelike talking head videos, the EMO framework takes a unique approach by adopting a direct audio-to-video synthesis strategy.
Unlike traditional, cumbersome processes that rely on 3D models or facial landmarks, EMO’s simplicity raises the question: can such simplicity truly achieve the desired outcome?
At the core of the EMO framework is a text-to-image model known as Stable Diffusion… Read the full blog for free on Medium.
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Published via Towards AI