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emo's Introduction

EMO

Emote Portrait Alive: Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions

Linrui Tian, Qi Wang, Bang Zhang, Liefeng Bo,

Institute for Intelligent Computing, Alibaba Group

YouTube

pipeline

Citation

@misc{tian2024emo,
      title={EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions}, 
      author={Linrui Tian and Qi Wang and Bang Zhang and Liefeng Bo},
      year={2024},
      eprint={2402.17485},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

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emo's Issues

[Non-Official Updates] Follow-up plans for the project

Thank you all for your incredible support and interest in our project. We've received lots of inquiries regarding a demo or the source code. We want to assure you that we are actively working on preparing the demo and code for public release. Although we cannot commit to a specific release date at this very moment, please be certain that the intention to provide access to both the demo and our source code is firm.

Our goal is to not only share the code but also ensure that it is robust and user-friendly, transitioning it from an academic prototype to a more polished version that provides a seamless experience. We appreciate your patience as we take the necessary steps to clean, document, and test the code to meet these standards.

Thank you for your understanding and continuous support.

HumanAIGC/AnimateAnyone#12

This kinda start needs to start being removed from Github.

While the paper is very detailed, and will help anyone with the know how and compute to reproduce this, i think the idea of using SD1.5 as a starting base, and AD, kinda means you really should be releasing these models. You are building on the literal compute of others, and in the case, its most likely only fair to return the favor.

Combined with many of the concepts coming from the open source community, such as ReferenceNet with originated from the ControlNet devs.

Or at least dont make these sort of github where you just seeking exposure, this is a code repo after all.

The animation has lots of physical object interactions e.g. lighting, reflection in glass, movement of earrings etc.

These are highly unlikely with the current algorithmic training architecture stated in the paper.
Please release the code and preliminary model for us to verify.
Even boximator in TikTok cannot reproduce such quality. Both do not release the codes as usual and hide behind marketing.
It just show that such deepfakes are now high quality and users should be wary of adversarial attacks like this from now on.
Please feel free to contact us at Amaris.AI if you need defences against such deepfakes!

code release time

thanks for your fabulous work , its really amazing and I couldn't wait to release code. could you please tell me when you're going to release the code 💥

Unreasonably high quality animations

This is for sure one of those researches that I'm sceptic about. The animation is just TO good to be img2video from audio. Muscles are moving, backgrounds are visible in the animation that is not visible in the image, 3D head rotations, while small, are impossibly good, hair jiggle corresponding to the laws of physics...

Nah... I believe it when I can try it and verify it. Until then it's to good to be true!

Fake

devs didn't make anything, this is fake.

混github好多年了,第一次看到issues中几乎100%骂的。如果太没有效果,也不会骂;骂是因为觉得好玩有点效果但不开源。 阿里也确实是找骂,因为github本来是放代码的,你占个坑就是找骂。 最好是删除,弄一个project页面就好了。 本来整一个也不是特别难,也公开了算法,大家别骂了。

要论文,不够;
要代码,还不够;
要权重,还不够;
要数据,还不够;
要debug,还不够;
要tunning,还不够;
要......

哈哈哈哈哈
人家算法结构图给了,描述的也比较清楚,大家就不要骂了。差不多得了。

Code Release

Wow this is fantastic great work!

Are you planning on releasing the code?

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