Comments (1)
Hi @dsGonz ,
Thanks for your interest in this. Where you have low texture regions, this breaks a fundamental assumption of self-supervised training (i.e. that depths can be recovered by matching pixels between camera views). Finding a method to fix this problem is a research problem in itself, and if you have interest and opportunity the community would be interested in efforts you make in this direction. Certainly some of the things you have suggested might work, or you could somehow detect low-texture regions and downweight their influence in the loss.
I agree that going for frame ids -1 0 +1
for a 30fpd sequence might be too small a baseline in general. You could consider using frame ids more widely spaced, e.g. -2 0 +2
or perhaps even more.
from monodepth2.
Related Issues (20)
- Network inference time problem
- The requested array has an inhomogeneous shape after 1 dimensions. HOT 5
- Write split file HOT 2
- obtained some very strange depth maps HOT 4
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- Questions about the meaning of grid in the F.grid_sample function
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- The new constraint about pose is not useful?
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