FisheyeDistill: Self-Supervised Monocular Depth Estimation with Ordinal Distillation for Fisheye Cameras. (arXiv:2205.02930v1 [cs.CV])

In this paper, we deal with the problem of monocular depth estimation for
fisheye cameras in a self-supervised manner. A known issue of self-supervised
depth estimation is that it suffers in low-light/over-exposure conditions and
in large homogeneous regions. To tackle this issue, we propose a novel ordinal
distillation loss that distills the ordinal information from a large teacher
model. Such a teacher model, since having been trained on a large amount of
diverse data, can capture the depth ordering information …

arxiv cameras cv distillation ordinal