How does the surface normal GT annotation of NYUv2 comes out?

[Boatsure]

This question is not targeted at your work, but a doubt that arises during the process of my investigating dense prediction research.

How the hell the normal GT is calculated from RGBD images？

Let's say, for example, the NYUv2 dataset.
There is no ready-made normal data in the NYUv2 homepage, and its paper is also vague about the method of calculating normals
(Fig.1. Given an input image with raw and inpainted depth maps, we compute surface normals and align them to the room by finding three dominant orthogonal directions.).

While all research are making normal estimation evaluation on NYUv2, what normal GT are they using?

Would you please share the code to generate the normal GT from RGBD images？
How are the normal GT in DSINE generated？
In addition to the official NYUv2 datasets, are there any pre-processed NYUv2 datasets that are used by the mainstream?

Thanks a lot！

[haodong2000]

Hi @Boatsure thanks for your interests!

Unfortunately, we just borrowed the surface normal benchmark provided in DSINE. So I may not be able to answer your questions.