2022
Uncertainty-Aware Self-Improving Framework for Depth Estimation
RA-L 2022
In recent years, self-supervised paradigms for depth estimation have drawn lots of attention from the community. Promising as they are, in order to achieve wider application and better performance, reasoning about the uncertainty of the estimated depth maps is in great demand. In this paper, we prop