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Adaptive 3D Face Reconstruction From Unconstrained Photo Collections
AbstractGiven a collection of "in-the-wild" face images captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of an individual along with albedo information. Motivated by the success of recent face reconstruction techniques on large photo collections, we extend prior work to adapt to low quality photo collections with fewer images. We achieve this by fitting a 3D Morphable Model to form a personalized template and developing a novel photometric stereo formulation, under a coarse-to-fine scheme. Superior experimental results are reported on synthetic and real-world photo collections.
Related Material
[pdf][bibtex]@InProceedings{Roth_2016_CVPR,
author = {Roth, Joseph and Tong, Yiying and Liu, Xiaoming},
title = {Adaptive 3D Face Reconstruction From Unconstrained Photo Collections},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}
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