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Paper

Detailed Human Avatars from Monocular Video

MPS-Authors
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Alldieck,  Thiemo
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Xu,  Weipeng
Computer Graphics, MPI for Informatics, Max Planck Society;

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Theobalt,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

/persons/resource/persons118756

Pons-Moll,  Gerard
Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society;

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Fulltext (public)

arXiv:1808.01338.pdf
(Preprint), 7MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Alldieck, T., Magnor, M. A., Xu, W., Theobalt, C., & Pons-Moll, G. (2018). Detailed Human Avatars from Monocular Video. Retrieved from http://arxiv.org/abs/1808.01338.


Cite as: http://hdl.handle.net/21.11116/0000-0002-5E0F-6
Abstract
We present a novel method for high detail-preserving human avatar creation from monocular video. A parameterized body model is refined and optimized to maximally resemble subjects from a video showing them from all sides. Our avatars feature a natural face, hairstyle, clothes with garment wrinkles, and high-resolution texture. Our paper contributes facial landmark and shading-based human body shape refinement, a semantic texture prior, and a novel texture stitching strategy, resulting in the most sophisticated-looking human avatars obtained from a single video to date. Numerous results show the robustness and versatility of our method. A user study illustrates its superiority over the state-of-the-art in terms of identity preservation, level of detail, realism, and overall user preference.