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why the localNet not use global depth prediction as input

Open q5390498 opened this issue 2 years ago • 4 comments

I am confuse that the dense depth is generated, why not use it as localnet's input? Does instead the guidance map to global depth prediction will bad to the accuracy?

q5390498 avatar Apr 21 '22 11:04 q5390498

Not sure I understand your question. The ground truth (i.e. "dense depth") can not be used as an input during training. We need to predict it after all. What would you do at test time?

wvangansbeke avatar Apr 21 '22 11:04 wvangansbeke

Thank for reply. The global net has generate global depth prediction, conf weights, guidence map, I mean why you need guidence map as localnet's input? why donot you use global depth prediction as localnet's input directly?

q5390498 avatar Apr 22 '22 03:04 q5390498

Hi @q5390498 ,

Ok makes sense. I believe that would work fine. Maybe quickly try it out. However, keep in mind that fusion takes place at multiple stages in the latest version. I remember that early + late fusion was the best strategy.

wvangansbeke avatar Apr 22 '22 04:04 wvangansbeke

Thank you very much. In localnet, we use the sparse depth map A and guidence map B as inputs, suppose we also use A as gt, does it make sense? I know the kitti dataset has more densely gt, but maybe it is hard to make custom dataset. Or can you give me some suggestions?

q5390498 avatar Apr 22 '22 04:04 q5390498