How to test on real-world images

[mikqs]

Hello,

Could you please explain how one can use real-world images after training the model ? I have tested the model successfully on the validation dataset from VTD, but for real-world data, I believe that I have to semantically segment it with the color palette that was used for training. Is there an existing model that you recommend for segmentation ? (i.e. which model do you use to label the left-most real-world input pictures of Fig. 6 from the paper ?)

Thank you

Originally posted by @mikqs in #16 (comment)

[lreiher]

You are correct that our proposed methodology takes semantically segmented camera images as input. As stated in our paper, we have used an in-house semantic segmentation model for the real-world examples shown in the paper.

We don't specifically recommend any model for semantic segmentation, but naturally, a better semantic segmentation model would also provide better input for Cam2BEV. There should be plenty of semantic segmentation methods publicly available, one starting point might be to take a look at paperswithcode.