I was checking the ground-truth depth maps in the training dataset. I came across several images in which sky depth is not invalid but rather it has values like 35000 or so.
However, similar depth values (35000 or so) are also assigned to far away objects, such as walls in some images.
For e.g., check out images 120.png and 131.png, the sky region in image 120.png has depth value like 37000, whereas the distant wall in image 131.png also has depth values like 37000.
I was expecting that sky regions will contain the invalid depth label, i.e., 0 but that is not the case in many images. I am wondering how can we train the DNN properly with such depth labelling or I am missing something? Please clarify.