EMO: Emote Portrait Alive (AliBaba)

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

EMO, an expressive audio-driven portrait-video generation framework. Input a single reference image and the vocal audio, e.g. talking and singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses, meanwhile, we can generate videos with any duration depending on the length of input video.

Overview of the proposed method.

Our framework is mainly constituted with two stages. In the initial stage, termed Frames Encoding, the ReferenceNet is deployed to extract features from the reference image and motion frames. Subsequently, during the Diffusion Process stage, a pretrained audio encoder processes the audio embedding.

The facial region mask is integrated with multi-frame noise to govern the generation of facial imagery. This is followed by the employment of the Backbone Network to facilitate the denoising operation. Within the Backbone Network, two forms of attention mechanisms are applied: Reference-Attention and Audio-Attention. These mechanisms are essential for preserving the character's identity and modulating the character's movements, respectively. Additionally, Temporal Modules are utilized to manipulate the temporal dimension, and adjust the velocity of motion.

EMOhumanaigc.github.io

https://humanaigc.github.io/emote-portrait-alive/

Various Generated Videos

Singing

Make Portrait Sing Input a single character image and a vocal audio, such as singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses, meanwhile, we can generate videos with any duration depending on the length of input audio. Our method can also persist the characters' identifies in a long duration.

Different Language & Portrait Style

Our method supports songs in various languages and brings diverse portrait styles to life. It intuitively recognizes tonal variations in the audio, enabling the generation of dynamic, expression-rich avatars.

Rapid Rhythm

The driven avatar can keep up with fast-paced rhythms, guaranteeing that even the swiftest lyrics are synchronized with expressive and dynamic character animations.

Talking Talking With Different Characters

Our approach is not limited to processing audio inputs from singing, it can also accommodate spoken audio in various languages. Additionally, our method has the capability to animate portraits from bygone eras, paintings, and both 3D models and AI generated content, infusing them with lifelike motion and realism.

Cross-Actor Performance

Explore the potential applications of our method, which enables the portraits of movie characters delivering monologues or performances in different languages and styles. we can expanding the possibilities of character portrayal in multilingual and multicultural contexts.