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2. Generalizable One-shot 3D Neural Head Avatar
 
 # Generalizable One-shot 3D Neural Head Avatar

  ![](/sites/default/files/publications/teaser_3.gif) 

 We present a method that reconstructs and animates a 3D head avatar from a single-view portrait image. Existing methods either involve time-consuming optimization for a specific person with multiple images, or they struggle to synthesize intricate appearance details beyond the facial region. To address these limitations, we propose a framework that not only generalizes to unseen identities based on a single-view image without requiring person-specific optimization, but also captures characteristic details within and beyond the face area (e.g. hairstyle, accessories, etc.). At the core of our method are three branches that produce three tri-planes representing the coarse 3D geometry, detailed appearance of a source image, as well as the expression of a target image. By applying volumetric rendering to the combination of the three tri-planes followed by a super-resolution module, our method yields a high fidelity image of the desired identity, expression and pose. Once trained, our model enables efficient 3D head avatar reconstruction and animation via a single forward pass through a network. Experiments show that the proposed approach generalizes well to unseen validation datasets, surpassing SOTA baseline methods by a large margin on head avatar reconstruction and animation.



 ## Authors



[Xueting Li](/index.php/person/xueting-li)

[Shalini De Mello](/index.php/person/shalini-de-mello)

[Sifei Liu](/index.php/person/sifei-liu)

[Koki Nagano](/index.php/person/koki-nagano)

[Umar Iqbal](/index.php/person/umar-iqbal)

[Jan Kautz](/index.php/person/jan-kautz)

 

 

 ## Publication Date



Monday, December 11, 2023

 

 ## Published in



[Advances in Neural Information Processing Systems (NeurIPS) 2023](https://neurips.cc/)

 

 ## Research Area



[Computer Vision](/index.php/research-area/computer-vision)

 

 

 ## External Links



[Project Page](https://research.nvidia.com/labs/lpr/one-shot-avatar/)

[Code](https://github.com/NVlabs/GOHA)

[ArXiv](https://arxiv.org/abs/2306.08768)

 

 

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