In a leap forward in generative ai, Meta ai has recently introduced a revolutionary technology called Audio2Photoreal. This cutting-edge project, designed as an open source initiative, enables the generation of realistic full-body 3D avatars based on audio input. The avatars not only display realistic facial expressions, but also imitate full body movements and gestures corresponding to words spoken in multi-person conversations. Let's delve into the intricacies of this revolutionary technology.
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How Audio2Photoreal works
Audio2Photoreal employs a sophisticated approach that combines the sample diversity of vector quantization with high-frequency detail obtained through diffusion, resulting in more dynamic and expressive motion. The process involves several key steps:
- Data set capture: The model first captures rich data sets of two-person conversations to facilitate realistic reconstructions.
- Construction of the movement model: From the data, it constructs a composite motion model, which includes facial, postural, and body motion models.
- Facial motion generation: Simultaneously, the model processes the audio using a pre-trained lip regressor to extract facial motion features. A conditional diffusion model then generates facial expressions based on these features.
- Generation of body movement: The audio input is then used to autoregressively generate poses guided by vector quantization (VQ) at 1 frame per second. These, along with audio, are fed into a diffusion model to generate high-frequency body movements at 30 frames per second.
- Representation of virtual characters: The generated facial and body movements are ultimately passed to a virtual character renderer trained to produce realistic avatars.
- Results display: The end result displays realistic, full-bodied virtual characters that express subtle nuances in conversations.
Usage scenario example
Audio2Photoreal finds application in various scenarios, such as training models with collected voice data to generate personalized character avatars, synthesizing realistic virtual images from voice data of historical figures, and adapting character voice acting to 3D games and virtual spaces .
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Product characteristics
- Generate realistic human avatars from audio.
- Provides pre-trained models and datasets.
- Includes face and body models.
- Achieve high-quality avatar rendering.
- Offers open source PyTorch code implementation.
How to use Audio2Photoreal
To use Audio2Photoreal, users must enter audio data. The advanced models then generate realistic human avatars based on the provided audio, making them a valuable resource for developers and creators in digital media, game development or virtual reality.
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Our opinion
Audio2Photoreal's introduction of Meta ai marks a significant step in the realm of avatar generation. Its ability to capture the nuances of human gestures and expressions from audio shows its potential to revolutionize virtual interactions. The open source nature of the project encourages collaboration and innovation between researchers and developers, paving the way for the creation of high-quality, realistic avatars. As we witness the continued evolution of technology, Audio2Photoreal is a testament to the limitless possibilities at the intersection of audio and visual synthesis.
