Fight Ill-Posedness With Ill-Posedness: Single-Shot Variational Depth Super-Resolution From Shading

Bjoern Haefner, Yvain Quéau, Thomas Möllenhoff, Daniel Cremers; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018, pp. 164-174

Abstract


We put forward a principled variational approach for up-sampling a single depth map to the resolution of the companion color image provided by an RGB-D sensor. We combine heterogeneous depth and color data in order to jointly solve the ill-posed depth super-resolution and shape-from-shading problems. The low-frequency geometric information necessary to disambiguate shape-from-shading is extracted from the low-resolution depth measurements and, symmetrically, the high-resolution photometric clues in the RGB image provide the high-frequency information required to disambiguate depth super-resolution.

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[bibtex]
@InProceedings{Haefner_2018_CVPR,
author = {Haefner, Bjoern and Quéau, Yvain and Möllenhoff, Thomas and Cremers, Daniel},
title = {Fight Ill-Posedness With Ill-Posedness: Single-Shot Variational Depth Super-Resolution From Shading},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}