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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;

/persons/resource/persons206382

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

/persons/resource/persons45610

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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arXiv:1808.01338.pdf
(Preprint), 7MB

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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: https://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.