shape_as_points

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Thank you for great work I'm curious about what `train_overfit.lst` and `test_overfit.lst` mean in the preprocessed dataset which can be downloaded in [*Dataset for Learning-based Reconstruction*](https://github.com/autonomousvision/shape_as_points#dataset-for-learning-based-reconstruction)? I cannot find any...

Kitsunetic

I use SAP to reconstruct mesh from depth map input, while the result is somekind weird. It seems that SAP try to reconstruct closed shape. For those only one side...

l1346792580123

Pretrained model for the optimization-based version

2

Hi Songyou, Thanks again for sharing the code for your excellent work! Could you please provide the pretrained model of optimization-based version that are reported in your paper (there are...

Runsong123

is it only availble with existing dataset?

hanjoonwon

Hi, Thanks for the awesome work! I'm trying to generate mesh from my own point cloud (generated with [DiT3D](https://github.com/DiT-3D/DiT-3D), trained also on ShapeNet). I already did the pre-processing such that...

ardianumam

Hello For some reasons, I would like to preprocess the shapenet dataset by myself. While running process_shapenet.py, I found that the work is stopped at processing the point_rasterize function. How...

create7859

If we set a boundary value as 0.5 at surface point and keep scaling, will the grid values converge to 0(inside) or 1(outside)?

create7859

training epochs

1

Hello, I'm trying to train your learning based model and according to your config noise_large(or small) yaml files, it said, you trained the model 400,000 epochs. However, I have used...

create7859

When I try to run the program without any modification, there is ༛̥⃝ʺ̤ error triggered at optim.py:11 "from src.optimization import Trainer": terminate called after throwing an instance of 'std::bad_alloc' what():...

Devincool

Hello, great paper. I have successfully managed to run inference on this model via the Optimization based Model and it has produced some decent results but not quite what the...

NiluK