  Pano3D is a new benchmark for depth estimation from spherical panoramas. It
aims to assess performance across all depth estimation traits, the primary
direct depth estimation performance targeting precision and accuracy, and also
the secondary traits, boundary preservation, and smoothness. Moreover, Pano3D
moves beyond typical intra-dataset evaluation to inter-dataset performance
assessment. By disentangling the capacity to generalize to unseen data into
different test splits, Pano3D represents a holistic benchmark for $360^o$ depth
estimation. We use it as a basis for an extended analysis seeking to offer
insights into classical choices for depth estimation. This results in a solid
baseline for panoramic depth that follow-up works can build upon to steer
future progress.
