Loss function about fast-depth

[JVGD]

I was reading the paper and just wondering the same, came here and didn't find it either

[EryiXie]

I was reading the paper and just wondering the same, came here and didn't find it either

Hi, I will begin to try some loss function design next week. Once I have some useful results, I will report it here.

[YiLiM1]

I read the paper and found that the author in the experimental part mentioned to follow the training method of "Sparse-to-dense: depth prediction from sparse depth samples and a single image"and L1 loss was used in that paper. I tried to train the network with L1 loss, and the result was very bad.

[JVGD]

I used the "depth loss" in this paper and seems that the training is starting to converge.
.

I also suspect that I have a shitty dataset, and that is why I am getting so many noise (although you can see the depth more or less in some sense in the high level, there is a lot of noise, piwelwise)

[sunmengnan]

I used the "depth loss" in this paper and seems that the training is starting to converge.
.

I also suspect that I have a shitty dataset, and that is why I am getting so many noise (although you can see the depth more or less in some sense in the high level, there is a lot of noise, piwelwise)

which dataset are you using?