  A typical monocular depth estimator is trained for a single camera, so its
performance drops severely on images taken with different cameras. To address
this issue, we propose a versatile depth estimator (VDE), composed of a common
relative depth estimator (CRDE) and multiple relative-to-metric converters
(R2MCs). The CRDE extracts relative depth information, and each R2MC converts
the relative information to predict metric depths for a specific camera. The
proposed VDE can cope with diverse scenes, including both indoor and outdoor
scenes, with only a 1.12\% parameter increase per camera. Experimental results
demonstrate that VDE supports multiple cameras effectively and efficiently and
also achieves state-of-the-art performance in the conventional single-camera
scenario.
