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We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D heads with compelling dynamic details under full disentangled control over camera poses, facial expressions, head shapes, articulated neck and jaw poses.
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Yiyu Zhuang, Hao Zhu, Xusen Sun, and Xun Cao · 2021
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Generative neural articulated radiance fields
Alexander W Bergman, Petr Kellnhofer, Yifan Wang, Eric R Chan, David B Lindell, and Gordon Wetzstein · 2022
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Efficient geometry-aware 3d generative adversarial networks
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Alias-free generative adversarial networks
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Controllable 3d face synthesis with conditional generative occupancy fields
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Explicitly controllable 3d-aware portrait generation
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Neural fields in visual computing and beyond
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Avatargen: a 3d generative model for animatable human avatars
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Im avatar: Implicit morphable head avatars from videos
Yufeng Zheng, Victoria Fernández Abrevaya, Marcel C Bühler, Xu Chen, Michael J Black, and Otmar Hilliges · 2022
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