2018
AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation
CVPR 2018poster
Supervised deep learning methods have shown promising results for the task of monocular depth estimation; but acquiring ground truth is costly, and prone to noise as well as inaccuracies. While synthetic datasets have been used to circumvent above problems, the resultant models do not generalize wel…