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Want to create an avatar from a single image? FlexAvatar is a transformer model that creates full 360°, high-quality, and expressive 3D head avatar from just a single portrait image in minutes. Real-time Demo: FlexAvatar's lightweight architecture allows both animation and rendering in real-time, enabling interactive user experiences. To... create a new 3D head avatar, only one image is required, e.g., from a webcam. The final avatar is ready after 2 minutes. Architecture: Under the hood, FlexAvatar adopts a transformer-based encoder-decoder design. The encoder maps the input image onto a latent avatar space, while the decoder produces 3D Gaussian attribute maps by incorporating the animation signal via cross-attention. The model learns all facial animations directly from the data without relying on pre-built 3D face models. This equips the avatars with realistic facial expressions. The internal avatar latent space can be conveniently used to integrate additional observations of a person via fitting. This enables use-cases where more than one image of a person is available, e.g., from a phone scan of the person. We train jointly on 2D monocular videos and multi-view data. However, in monocular videos, the animation signal leaks the target viewpoint, causing the model to produce incomplete 3D heads. We call this phenomenon entanglement of driving signal and target viewpoint. To prevent entanglement, we introduce bias sinks. These are learnable tokens that indicate whether a training sample stems from a monocular or a multi-view dataset. During training, the model learns to produce incomplete 3D heads only when the monocular token is present. During inference, FlexAvatar then always uses the multi-view token for which the model has learned to produce complete 3D heads. This simple design allows to combine the generalizability from monocular data with the quality of multi-view data. FlexAvatar summary: - Input: Single-image, phone scan, or monocular video - Output: Full 360° head avatar - Expressive animations - Real-time rendering and animation - Generalization to any portrait - Create a new avatar in 2 minutes - Use bias sinks to combine 2D and 3D data 🏠 🌍 🎥 Great work by Tobias Kirschstein and Simon Giebenhain!show more

Matthias Niessner

49,709 subscribers

96,371 Aufrufe • vor 9 Monaten •via X (Twitter)

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10 Kommentare

Profilbild von Luis

Luisvor 9 Monaten

I hope the code or a demo really is coming soon. We already saw a couple like this and at the end nothing is released.

Profilbild von MetaDJ

MetaDJvor 9 Monaten

WOW ✨

Profilbild von Karan Jagtiani

Karan Jagtianivor 9 Monaten

Impressive approach! The use of bias sinks for differentiating training data types is clever. How well does it handle varying lighting conditions in the input images?

Profilbild von 0xLady

0xLadyvor 9 Monaten

bro this is actually insane single pic to full 360 expressive head in 2 mins? we eating good in 2025bro this bias sink trick is actually genius entanglement solved in one line of code im stealing this for my next 3d mint legendary work fam

Profilbild von Lewis N Watson

Lewis N Watsonvor 9 Monaten

woah

Profilbild von KellyV

KellyVvor 3 Monaten

Great job

Profilbild von Torsion

Torsionvor 9 Monaten

This is what Meta should have done

Profilbild von Andy Wojcicki

Andy Wojcickivor 9 Monaten

nice flex! 😉

Profilbild von Himanshu Kumar

Himanshu Kumarvor 9 Monaten

FlexAvatar's transformer model generates a 3D avatar within a processing time of minutes.

Profilbild von Risichad 🦾

Risichad 🦾vor 9 Monaten

Impressive !

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48,280 Aufrufe • vor 2 Jahren

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11,458 Aufrufe • vor 3 Jahren

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AK

38,686 Aufrufe • vor 2 Jahren