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Delivering immersive, 3D experiences for human communication requires amethod to obtain 360 degree photo-realistic avatars of humans. To make theseexperiences accessible to all, only commodity hardware, like mobile phonecameras, should be necessary to capture the data needed for avatar creation.For avatars to be rendered realistically from any viewpoint, we requiretraining images and camera poses from all angles. However, we cannot rely onthere being trackable features in the foreground or background of all imagesfor use in estimating poses, especially from the side or back of the head. Toovercome this, we propose a novel landmark detector trained on synthetic datato estimate camera poses from 360 degree mobile phone videos of a human headfor use in a multi-stage optimization process which creates a photo-realisticavatar. We perform validation experiments with synthetic data and showcase ourmethod on 360 degree avatars trained from mobile phone videos.

Photo-realistic 360 Head Avatars in the Wild