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Published 20 hours ago • verified publisher icon fangchangma

Different sparse input when each sample input is loaded

Open TruongKhang opened this issue 4 years ago • 3 comments

Hi, I have read your implementation and I have a question about your implementation of sparse depth input generation in NYU dataset. You generated the sparse input when the ground truth depth is loaded by dense_to_sparse function. But this sparse input maybe not the same at the next epoch when the ground truth depth is loaded again. Do I understand correctly? If I misunderstand something, please explain it for me!

Thanks,

TruongKhang avatar Apr 12 '20 08:04 TruongKhang

Hey @TruongKhang. You were right - the exact sampling pattern changes from frame to frame, and from epoch to epoch. This randomization is by design, such that the network does not overfit a particular set of sampling patterns.

fangchangma avatar Apr 13 '20 02:04 fangchangma

@fangchangma , is it reasonable when compared with the baseline methods? The input now is different for all methods.

TruongKhang avatar Apr 13 '20 07:04 TruongKhang

is it reasonable when compared with the baseline methods

Which baseline methods were you referring to?

fangchangma avatar Apr 14 '20 08:04 fangchangma