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.

Pano3D 是一个新的基准测试，在全景照片深度估计技术中评估性能，主要目标是精度和准确性，次要目标是边界保留和平滑性。利用不同的测试数据集，Pano3D 不仅可以评估同一数据集内的性能，还可以评估推广到不可见数据的能力。我们在此基础上进行了扩展分析，从而为全景深度估计领域提供了坚实的基础。后续研究可以在此基础上继续推动进步。