Question about preparing the training data. about d2-net HOT 2 CLOSED

Hello. Please find the answers inlined below.

Then why you need to crop the images insteaded of use the origin image?

You are right, we are using crops due to memory reasons mainly. Another reason for using crops is that training images have a wide range of resolutions.

and what do you mean by a random 256 * 256 crop centered around one correspondence? around which correspondence?

The pipeline for dataset selection first picks a correspondence from the sparse 3D model and then crops a 256x256 area around it.

After that, do you choose a fixed number of pixel-wise correspondence as your positive pair or use all of them? and how can you guarantee this two cropped images have at least 128 correspondence pixel pairs ?

We use all pixel-wise correspondences for computing the loss. Since we are using a batch size of 1, we simply skip the image pairs with fewer than 128 correspondences.

from d2-net.

Thanks a lot !

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