Mu Hu

I have not conducted experiments under a similar setting. But I guess there could be two main reasons: (1) The groundtruth data you used is not dense enough to support...

You could refer to [1]【PNConv-CNN】CVPR2020 Uncertainty Aware CNNs for Depth Completion Uncertainty from Beginning to End. [2] 【PwP】ICCV2019 Depth Completion From Sparse LiDAR Data With Depth-Normal Constraints. for better understanding...

Thanks for your interest! 1. The one-frame sparse depth maps as inputs are of about 5% density of all pixels while the groundtruth depth maps are of 15%. The groundtruth...

> Thank you for your quick reply. > > 1. So the ground truth depth maps with 15% sparsity are used as supervision? Thanks for the references, I will check...

> Okay I understand regarding the sparsity for training. > > But I am still unsure about what the positional encodings are because I am preparing my own data, so...

> I get it now, I was able to create the positional encoding (u, v coordinates using the camera intrinsic). I still get a patchy result like [this](https://drive.google.com/drive/folders/1d-maw_Yrix_JoHldWCof8v1Mwx2rLvs6?usp=sharing) when I...

> But we dont need GT maps in this case where we just evaluate. The result that I've shared here is not based on fine-tuning but merely test_completion I think...

Thanks for your interest! But we have never encountered such problems. Maybe you could check the completeness your dataset and environments.

> PyTorch profiler Thanks for your interest! I have not used pytorch profile before. I would probably try it recently, but it will take some days.

> Hi there, thank you very much for your excellent work and for publishing it. > > I am trying to implement a "light weight" version of the ENet which...