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arXiv · 2207.07621

MegaPortraits: One-shot Megapixel Neural Head Avatars

Nikita Drobyshev·Jenya Chelishev·Taras Khakhulin·Aleksei Ivakhnenko·Victor Lempitsky·Egor Zakharov
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Abstract

In this work, we advance the neural head avatar technology to the megapixel resolution while focusing on the particularly challenging task of cross-driving synthesis, i.e., when the appearance of the driving image is substantially different from the animated source image. We propose a set of new neural architectures and training methods that can leverage both medium-resolution video data and high-resolution image data to achieve the desired levels of rendered image quality and generalization to novel views and motion. We demonstrate that suggested architectures and methods produce convincing high-resolution neural avatars, outperforming the competitors in the cross-driving scenario. Lastly, we show how a trained high-resolution neural avatar model can be distilled into a lightweight student model which runs in real-time and locks the identities of neural avatars to several dozens of pre-defined source images. Real-time operation and identity lock are essential for many practical applications head avatar systems.

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Nikita Drobyshev, Jenya Chelishev, Taras Khakhulin, Aleksei Ivakhnenko, Victor Lempitsky, Egor Zakharov. 2023-03-28. MegaPortraits: One-shot Megapixel Neural Head Avatars. https://arxiv.org/abs/2207.07621

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