Monocular depth estimation is an ill-posed problem as the same 2D image can be projected
from infinite 3D scenes. Although the leading algorithms in this field have reported …

Self-supervised monocular depth estimation (MDE) models universally suffer from the
notorious edge-fattening issue. Triplet loss, popular for metric learning, has made a great …

The Wasserstein distance has been employed for determining the distance between point
clouds, which have variable numbers of points and invariance of point order. However, the …

Deep learning has proved to be a breakthrough in depth generation. However, the
generalization ability of deep networks is still limited, and they cannot maintain a satisfactory …

We present an unsupervised simultaneous learning framework for the task of monocular
camera re-localization and depth estimation from unlabeled video sequences. Monocular …

Self-supervised learning for monocular depth estimation has been widely investigated as an
alternative to the supervised learning approach. Uncertainty estimation in depth estimation …

Self-supervised monocular depth estimation has been widely investigated to estimate depth
images and relative poses from RGB images. This framework is promising because the …